{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9e01488e-1767-470e-9dbc-3d198dc1b1d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ee52b555-8848-497e-9c01-a879001adca4",
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.0</td>\n",
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      ],
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       "   手机上网整体满意度  网络覆盖与信号强度  手机上网速度  手机上网稳定性  套外流量费（元）  套外流量（MB）  脱网次数  当月MOU  \\\n",
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       "3          9          8       8        7       0.0       0.0   0.0   1930   \n",
       "4         10         10      10       10       0.0       0.0   0.0     18   \n",
       "\n",
       "   微信质差次数  上网质差次数  ...  爱奇艺_-1  爱奇艺_1  其他，请注明.4_-1  其他，请注明.4_98  其他，请注明.5_-1  \\\n",
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       "\n",
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      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "traindata=pd.read_csv('./ans1/traindata_clean_附件2.csv',encoding='gbk')\n",
    "traindata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c95f1dca-fd78-4224-9416-8ae7f854c0cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "   用户id  套外流量费（元）  套外流量（MB）  脱网次数  当月MOU  微信质差次数  上网质差次数  部落冲突_-1  部落冲突_8  \\\n",
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       "4     5       0.0       0.0    52    110       0       0        1       0   \n",
       "\n",
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       "4            0      1     0        1       0  \n",
       "\n",
       "[5 rows x 126 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testdata=pd.read_csv('./ans1/testdata_clean_附件4.csv',encoding='gbk')\n",
    "testdata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f6e97594-36f5-4e9e-8d00-cfa7ecc63096",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['梦幻诛仙_6',\n",
       " '办公室_2',\n",
       " '套外流量（MB）',\n",
       " '客户星级标识_白金卡',\n",
       " '和平精英_1',\n",
       " '手机QQ_-1',\n",
       " '穿越火线_-1',\n",
       " '客户星级标识_未评级',\n",
       " '高铁_-1',\n",
       " '手机支付较慢_5',\n",
       " '农村_-1',\n",
       " '全部都卡顿_99',\n",
       " '性别_男',\n",
       " '穿越火线_3',\n",
       " '其他，请注明.2_98',\n",
       " '其他，请注明_98',\n",
       " '是否5G网络客户_否',\n",
       " '火山_8',\n",
       " '其他，请注明.2_-1',\n",
       " '龙之谷_5',\n",
       " '高校_3',\n",
       " '梦幻西游_4',\n",
       " '办公室_-1',\n",
       " '炉石传说_-1',\n",
       " '下载速度慢_4',\n",
       " '芒果TV_-1',\n",
       " '咪咕视频_-1',\n",
       " '优酷_-1',\n",
       " '全部游戏都卡顿_99',\n",
       " '其他，请注明.3_98',\n",
       " '今日头条_6',\n",
       " '客户星级标识_银卡',\n",
       " '打开网页或APP图片慢_3',\n",
       " '梦幻西游_-1',\n",
       " '抖音_-1',\n",
       " '和平精英_-1',\n",
       " '欢乐斗地主_-1',\n",
       " '全部游戏都卡顿_-1',\n",
       " '今日头条_-1',\n",
       " '阴阳师_10',\n",
       " '欢乐斗地主_7',\n",
       " '微信_1',\n",
       " '其他，请注明.5_-1',\n",
       " '全部网页或APP都慢_-1',\n",
       " '爱奇艺_-1',\n",
       " '其他，请注明.5_98',\n",
       " '芒果TV_4',\n",
       " '手机上网速度慢_4',\n",
       " '其他，请注明.1_-1',\n",
       " '淘宝_-1',\n",
       " '商业街_4',\n",
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       " '居民小区_1',\n",
       " '上网过程中网络时断时续或时快时慢_3',\n",
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       " '商业街_-1',\n",
       " '快手_7',\n",
       " '淘宝_3',\n",
       " '其他，请注明.4_98',\n",
       " '网络信号差/没有信号_-1',\n",
       " '全部网页或APP都慢_99',\n",
       " '地铁_-1',\n",
       " '腾讯视频_-1',\n",
       " '客户星级标识_二星',\n",
       " '搜狐视频_5',\n",
       " '龙之谷_-1',\n",
       " '新浪微博_7',\n",
       " '京东_-1',\n",
       " '百度_-1',\n",
       " '客户星级标识_一星',\n",
       " '梦幻诛仙_-1',\n",
       " '快手_-1',\n",
       " '拼多多_-1',\n",
       " '手机支付较慢_-1',\n",
       " '是否不限量套餐到达用户_否',\n",
       " '全部都卡顿_-1',\n",
       " '王者荣耀_2',\n",
       " '脱网次数',\n",
       " '部落冲突_8',\n",
       " '套外流量费（元）',\n",
       " '其他，请注明.4_-1',\n",
       " '王者荣耀_-1',\n",
       " '网络信号差/没有信号_1',\n",
       " '性别_女',\n",
       " '火山_-1',\n",
       " '炉石传说_9',\n",
       " '微信质差次数',\n",
       " '阴阳师_-1',\n",
       " '上网过程中网络时断时续或时快时慢_-1',\n",
       " '性别_性别不详',\n",
       " '是否不限量套餐到达用户_是',\n",
       " '咪咕视频_9',\n",
       " '拼多多_8',\n",
       " '手机上网速度慢_-1',\n",
       " '显示有信号上不了网_-1',\n",
       " '抖音_6',\n",
       " '居民小区_-1',\n",
       " '其他，请注明.3_-1',\n",
       " '京东_4',\n",
       " '当月MOU',\n",
       " '高铁_7',\n",
       " '客户星级标识_三星',\n",
       " '打游戏延时大_-1',\n",
       " '手机QQ_2',\n",
       " '高校_-1',\n",
       " '部落冲突_-1',\n",
       " '打开网页或APP图片慢_-1',\n",
       " '微信_-1',\n",
       " '搜狐视频_-1',\n",
       " '客户星级标识_金卡',\n",
       " '显示有信号上不了网_2',\n",
       " '腾讯视频_3']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "setcols=list(set(traindata.columns).intersection(set(testdata.columns)))  \n",
    "setcols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "207b12e1-ba5c-44db-8524-bb92b127cf84",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.tree import plot_tree\n",
    "\n",
    "from sklearn import tree\n",
    "\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "617f5520-d13b-4cbc-8595-a198e0c32d4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "Y1=traindata[traindata.columns[0]]\n",
    "Y2=traindata[traindata.columns[1]]\n",
    "Y3=traindata[traindata.columns[2]]\n",
    "Y4=traindata[traindata.columns[3]]\n",
    "X=traindata[setcols]\n",
    "test_X=testdata[setcols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "33d98cab-8147-4d9a-9cd1-d09237254d7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "全部数据训练效果\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       1.00      0.99      0.99       458\n",
      "           2       1.00      1.00      1.00        87\n",
      "           3       1.00      0.99      0.99       210\n",
      "           4       0.99      0.99      0.99       160\n",
      "           5       1.00      0.99      0.99       410\n",
      "           6       0.99      0.99      0.99       438\n",
      "           7       1.00      0.99      0.99       539\n",
      "           8       0.99      0.98      0.98      1005\n",
      "           9       0.97      0.97      0.97       857\n",
      "          10       0.98      0.99      0.98      2856\n",
      "\n",
      "    accuracy                           0.99      7020\n",
      "   macro avg       0.99      0.99      0.99      7020\n",
      "weighted avg       0.99      0.99      0.99      7020\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#选择决策树模型为：entropy。\n",
    "YY=Y1\n",
    "\n",
    "DT=DecisionTreeClassifier( criterion='entropy')\n",
    "\n",
    "see1=DT.fit(X,YY)\n",
    "\n",
    "y_pred=DT.predict(X)\n",
    "print('全部数据训练效果')\n",
    "print(classification_report(y_pred,YY))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "87680994-a16d-4aaa-840c-8a69dcbf07d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KpaWlsnLlSmXHjh3q/itXrqy0adNGSUhISHU/d+/eVW7cuJFqxmhqL19fX6Pxs2fPVkxMTNLNWrawsFAqV66c6vOrVq2qzJ49W71OKxN48eLF7/T9eV1ytu2br9ezWPPmzav0799fvQ4KClK0Wq2yevVqRVEU5c6dO8qKFSvU719oaKiSPXv2FBnhyRmzqXnXzGVA2bFjR4rxXl5eCmCUUT1//nxFr9crMTEx7/JWqNLLXD516pSiKIri7OysTJkyRVEURfn++++VTp06qePWrl2rjlu9erUCKI8ePVL3+d1336n3Y2Njlfz58yudO3dW25K/v/PmzXvrGlPj4+OjeHp6qtdPnjxRtFqtsnnzZkVRkr4P/H8WdrItW7YoOp1OURRFuX37tgIo69atU+9fvnxZadmypbqPmjVrKk2aNFHvJyQkKFmyZFGzk4OCghRAWbZsmdrn2LFjys2bN9PckxBCCPG5k5rLQgghhBDis5acoZyWr7/+OtX2/Pnzc/fuXWJjY5k8eTKdO3dm9uzZFChQgEmTJlGwYEEuX75M9uzZ/45lp+vFixfs2LEDExMT5s+fz7Bhw9i/fz/x8fFs376d6dOnpxgTHBxMkSJFmD17NpkzZ+bEiRN8+eWXnDx5EoDixYvz8OFDtS5xmzZtaNWqFeHh4Wr95kKFChEREaHO+eTJExo0aECNGjXo2rWrmq0JsH79esqWLUuXLl1YunSpUebv7du3KVWqFEeOHAHAz88PnU6Hs7MzoaGh+Pn5UaZMGWJiYnj27Bm5c+dOkSEeFxdHnjx50s3wHj9+POfOnUv1XmhoKE5OToSHhxMZGcmcOXOM6km/zmAwqDWrM2LTpk0UKlRIvU7+Ojw8HH9/f9zd3XF3dzcac+fOHQAKFChAeHg448aN4/jx4/j4+BAfH59mJva7SkxMTNHWoEEDmjVrlqL9ypUrAJQpUybFvQcPHvDFF1/8pbUky5EjB5BU7/r1r19XpUoV9ety5coBSRnXZmZmPHjwQM2aB9Dr9dSoUYMzZ84YzVGsWDH69ev3Xmt0dXUlLCyMfv36cfLkSXx9fUlMTDT6fpiYmBjVEHd0dCQ+Ph4AHx8fAKpWrareL1mypPqJCEh6v4OCglLsPfnPRObMmWnbti0DBgxg7969VKhQgWbNmhn9GRNCCCH+aSS4LIQQQgghPmuPHj3CzMwsxQF3Dx8+pFSpUuzbt4+KFSsa3YuNjVWDcDNmzODJkyf06dOH2bNnAzBkyBAAtm3bRrFixT7CLoxNnjyZSpUqUb9+fSZPnkzHjh0ZNWoUPXr0YO3atSxfvpwCBQoYjenRowc9evRAr9djamqKiYmJeiBeVFQUer1efY8SExOJj4/nq6++4vfff091DceOHWPUqFHY2tqyaNEiYmJiUBRFvZ8rVy62bdtG8+bNuXz5Mt7e3mqAeebMmTRo0IDcuXOr/Y8cOYKiKEydOpVSpUpha2urHgQIKQ9NjI2Nxc/PDycnpzTfp8TEREqWLJnqvadPn5I9e3aWL1/O2LFjiYuLQ6/XGwWRk/d06dIlihQpkuZz0lKoUCFcXV1TtCe/T5MnT6Zhw4ZG97JmzQoklYpo2bIl7dq1o3fv3lSoUIEePXpkeA1vevToUYq28uXLp9lfq9Vy7ty5FAFPZ2fnv7yWjHj9z1by300TExOj9vTGAJQtWzbNQyDfZuHChQwePJhu3boxYsQIKlWqRI0aNYz65MiRI83yKamtU1EUTp06RYECBdQ/x717905x+KidnZ369S+//MLx48c5fvw4v//+O2PHjmX79u2p/nJACCGE+CeQmstCCCGEEOKzlitXLhwdHbGzszN6JddVzpQpU4p7WbNmVYM9ZcqUYdy4cWpG5ev++OMPo4zKj+H69essW7aMCRMm0KtXL5YsWcKYMWMwGAzMnDmTrl27MnnyZCIjI1MdHxcXx6pVqxgwYAChoaGEhoZSo0YN3N3dCQ0NVesNBwcH89tvv6W5DlNTU4oVK8aJEyeoU6cOlpaWtGjRgnv37qHRaDA1NUWj0XDq1CkWLlyoBt0ePHjA2rVrGT16tNF8CxcupFOnTmzbto2FCxcSGRlJixYtiI2NTfHsp0+fMmbMGOLi4jh06BAPHz4kNjaWwYMHqxnc8fHxJCYmcuzYMQ4cOGA0PigoiMDAQHLkyMGQIUOIjo5m8eLFuLi4EBAQQEhICPfu3SNr1qxMnjz5vQLL6bGxscHZ2ZlXr17h6uqqvlauXKlmknt6elKlShXWrVvH999/T548eXjw4EGKuczNzdXs2DfpdDqjzNpz587h7+//zussXrw4CQkJaLVadY1arTbVetp/t2PHjqlfnzlzBo1GQ4ECBciaNSvOzs4cPXpUvR8fH8/x48fVDOd3lZwdn9r7uWrVKtq1a8fixYtp27YtlpaWBAUFGfV58xcgr0v+JUNyzWwAf39/qlWrpmbXFy9enKdPnxr9mdi1a5f6C54rV64wZswYqlevztixYzl58iQVK1bEw8MjQ/sUQgghPicSXBZCCCGEEP9qDRs2ZNSoUYBx9uG+fft49OgRrVu3TnXc4sWLOXTo0AdfT8+ePWnSpAlVq1YlU6ZMxMfH4+HhwZIlS7CxsWHkyJGsX78eKyurNOe4efOmUbAOoH///tja2mJnZ4etrS22trZ4eXmlOUelSpX4448/yJIlCydOnODp06esWbOGvHnzEhQUxIsXL6hUqRLFihUzKgUwbtw4qlevTtmyZdW2DRs2cPHiRcaOHcuWLVs4e/Ysu3fv5u7du0aHuiVr0qQJbm5uKIpCrVq1OHz4MCYmJhgMBjp16kRMTAznzp3DYDBw+PBhGjdubBTUO3bsGHZ2dhQsWFBt+/HHH8mTJw9t2rQhMDCQli1bUrFiRYYOHZru9+N9jR8/nsWLF/Pzzz9z4sQJBg8ezLJly8iTJw8AWbJk4fr16+zdu5dff/2VmjVr4u/vnyLw+eWXX/L8+XNWrVrFqVOnmDlzpprZW6pUKTZu3EhkZCS3bt2ic+fOODg4vPMaa9WqRfXq1Wnfvj07duzgwIEDdO7cmatXr6abMf53GDNmDFu2bGHTpk2MGTOG1q1bqyVpJkyYwPr16xk3bhyHDx+mXbt2PH36lJEjR2boGUWLFsXa2poZM2bg7e3N4sWLef78OZD0/fD29ubw4cNs2LCBatWqER4enmZg/02FChWidevWDB48GE9PTw4dOkTXrl3Jnz+/WtJj3Lhx7Ny5kzFjxnD8+HGmT5/OxIkT1X1aW1sza9Ys3NzcOHXqFJs3b+b69evky5cvQ/sUQgghPidSFkMIIYQQQvzjKIqi1pNNL9vwTQkJCcTHx/Py5Uv69OnDjz/+iL29vXpfr9cTFBREdHQ069evp0qVKtSuXVutz2pqamo0X1RUFKGhody8eTPFsxITE4mJiaF06dJGJQnWrVtnVLrh+++/J0eOHNSuXRtIytTOlStXinIWsbGxmJiYoNPp0Gq1Kfbt7u5Ot27dUqzDYDCg1+vVcgLJgcvXa/cmB78sLCxQFEWt2/ymHTt2sHbtWvbu3WvUXrNmTbWUR//+/alRowZ16tTBy8uL+Ph4Jk6cqPa9cuUKFy9eZOvWrej1emxsbAgLCwOSykx07doVU1NTfvzxRxwcHDh06BC9evXi22+/5fLly2TNmpWdO3dSvXr1FCUStmzZQunSpcmbNy/FihVj3bp1KcpBfChdu3YlKiqKuXPnMm7cOIoUKcLOnTupUKECAJMmTSIgIIDWrVtjY2NDp06dyJ49u5rZnKxgwYIsW7YMNzc3nj59SqFChdSA+MyZM/nuu+9wcnIid+7cTJ06Nc260mnZvn07gwYNokuXLmg0GurWrcucOXP+tvclLVOnTmXYsGG8fPmSRo0asXTpUvVe586dgaTv/4wZM/jyyy85cuQIhQsXztAzbGxs2LhxI4MHD8bNzQ1nZ2eaN28OwIIFC+jevTuNGjUia9as9OvXj82bN3Py5MlU/96kJjljf9iwYcTHx1OjRg1Wr16t/iLo66+/ZtOmTUycOJHZs2fj4uLCqlWraNGiBQAuLi78+uuvTJgwgVmzZmFubk7Tpk2N/n4IIYQQ/zQaJb0iV0IIIYQQQnxmnj9/zhdffEFYWBg2NjbcuXNHrXObnvj4ePR6PZ6enlhZWTFp0iS8vb2xtLRU+1y+fJl69erx/PlzrK2tOX78OK6urhQvXhx/f390unfPzYiLi8NgMBAREYG5uTn9+/fnypUr6WYTAzx+/JhVq1bxxx9/cO7cOaKiotBqtYwePZr58+er5SoURVEDzImJiWg0mhQBw/j4eKKjo7ly5Yp6aFhgYCAFChTgzJkzKQ4SW79+PUOHDuXZs2epru3JkycMHTqUDRs2oNFouH//Pvnz58fPz4+8efOqa3nx4gVOTk789ttvHD58GHd3d54+fYqTkxOjR4/Gx8eHffv2AUkBuaNHj6aoaWtra8svv/xCgwYNiI2NZdWqVfTo0YNnz57h4uLCunXraN68OS9fvuTatWscP36cHTt2EBgYSPny5fnjjz/Imzcv1apVo0iRIuTOnZu8efMaZVyLv5+Xlxe1atXi5cuXZMmS5VMvRwghhBAfmASXhRBCCCHEP87SpUvRaDQ0bNiQXLlyvdcc8fHxGQoW/1Xff/89Dx8+fGtwWVEUSpUqhaWlJR06dKBfv34fZ4Hv4caNGxQtWtQouPy6Pn36sGbNGrp06cKCBQvUdoPBYJS9nRFBQUHMnTuXsWPHsmzZMoYMGUKxYsUoX748LVq0oE6dOmi1WkJDQ9m3bx9eXl6cP3+eGzdusHLlStq1a/e+2xXvQYLLQgghxL+bBJeFEEIIIYQQf4vo6Gj0ev3fFsRPTEwkNjZWPcgtPcn/7PnY5SCEEEIIIf7NJLgshBBCCCGEEEIIIYQQIsNM3t5FCCGEEEIIIYQQQgghhDAmwWUhhBBCCCGEEEIIIYQQGSbBZSGEEEIIIYQQQgghhBAZJsFlIYQQQgghhBBCCCGEEBn29xzbLIT4R0lMTOTJkydYW1vLCepCCCGEEEIIIYQQ/3GKohAeHk6OHDkwMUk7P1mCy0IInjx5Qu7cuT/1MoQQQgghhBBCCCHEZ+TRo0fkypUrzfsSXBZCYG1tDST9wLCxsfnEqxFCCCGEEEIIIYQQn1JYWBi5c+dWY0ZpkeCyEEIthWFjYyPBZSGEEEIIIYQQQggB8NbyqXKgnxBCCCGEEEIIIYQQQogMk+CyEEIIIYQQQgghhBBCiAyT4LIQQgghhBBCCCGEEEKIDJPgshBCCCGEEEIIIYQQQogMk+CyEEIIIYQQQgghhBBCiAyT4LIQQgghhBBCCCGEEEKIDJPgshBCCCGEEEIIIYQQQogMk+CyEEIIIYQQQgghhBBCiAyT4LIQQgghhBBCCCGEEEKIDJPgshBCCCGEEEIIIYQQQogMk+CyEEIIIYQQQgghhBBCiAyT4LIQQgghhBBCCCGEEEKIDJPgshBCCCGEEEIIIYQQQogMk+CyEEIIIYQQQgghhBBCiAyT4LIQQgghhBBCCCGEEEKIDJPgshBCCCGEEEIIIYQQQogMk+CyEEIIIYQQQgghhBBCiAyT4LIQQgghhBBCCCGEEEKIDJPgshBCCCGEEEIIIYQQQogMk+CyEEIIIYQQQgghhBBCiAyT4LIQQgghhBBCCCGEEEKIDJPgshBCCCGEEEIIIYQQQogMk+CyEEIIIYQQQgghhBBCiAyT4LIQQgghhBBCCCGEEEKIDJPgshBCCCGEEEIIIYQQQogMk+CyEEIIIYQQQgghhBBCiAyT4LIQQgghhBBCCCGEEEL8Qz18+JDz588TGxv70Z8twWUhhBBCCCGEEEIIIYT4QHx9fSlXrhyZM2dm2LBhKIry1jETJkzA3t4eMzMzmjdvTnh4uNH9xMREKleuzOzZs43aBw8eTJkyZWjfvj0uLi7cvHnzg+7lbSS4LIQQQgghhBBCCCGEEB+AwWCgcePGfPnll5w/f57r16/j6emZ7pgNGzawYcMG9u/fz7Vr17hx4wbTp0836rN06VJCQ0Pp37+/2ubl5cWePXu4f/8+t2/fpm7duinG/d0kuCyEEEIIIYQQQgghhBAfwL59+wgNDWXOnDnkz5+fqVOnsmrVqnTHPHr0iDVr1lC+fHkKFChAmzZt8PHxUe8/efKE0aNHs2DBAvR6vdpuZmbGihUrsLGxAaB06dK8evXq79lYGnQf9WlCCCGEEEIIIYQQQgjxL3X58mUqVqyIpaUlACVLluT69evpjhk5cqTR9a1btyhYsKB6PXDgQPLkycOjR4/4888/qVy5MgCVKlVS+wQGBrJ69WqjzOaPQYLLQryj4OBgMmfOrF4PGTKEgIAANm3apLbdvXuXAgUKqNePHj0ib968FClSJNU5b9++zdGjR6lSpcrft/AMuOR3j0zWmT71MoQQQgghhBBCCCE+e1msbXF2zGrUFhYWhouLi3qt0WjQarUp4kppuX37Njt27ODixYsAeHt7s3XrVr755hvu3bvH5MmTqVevHgsXLlTHrFixggEDBlC9enW6du36gXb3biS4LMQ7iI+Pp1KlSnTp0oURI0YASR89MDMzU/ts2bKFTp06cfv2bXLnzg2AXq/HwsICX1/fVOfNmzev+tEFgJo1a3Ls2DHCwsKwtrbm22+/ZevWrfj5+ZE3b16WLl3KpEmTCA0N5dtvv2XJkiWYmZlRs2ZNmjVrxsCBAwHYuXMnAwcOxN/fP0P7rDFuMOjlx4IQQgghhBBCCCHE25ibmnJrvodRgFmn0xnFiwDMzc2Jiop6a3A5MTGRrl270q1bN4oVKwYkBY4rVKjAnj170Gg0dO/enTx58tCvXz8KFSoEwPfff0/27Nnp1asXCxcupG/fvh94p2mTKJIQ70Cn0+Hm5kbHjh2pXLky1apVw8TEBI1GA0BAQAADBgxgxIgRamAZSPHDJDWv18pJdv36dSpUqMC1a9fUtmPHjjFo0CDWrVtHoUKFaNWqFZMmTWLy5MkfYIf/L08psHX4cPMJIYQQQgghhBBC/BvFRBDjd5HA8FCj4LK9vX2KJMPw8HBMTU3fOuWkSZMICgri559/VtseP37MN998o8agcufOjaOjI/fu3VODy2ZmZjRq1IiXL1/i7u4uwWUhPkdt27Zl586dLFmyhGrVqhndGz9+PF9++SXjx483atdoNERHR1O8ePFU53zy5EmKNq1Wy7Vr1yhTpgz3799X29euXUvr1q1p1aoVAGPGjGH8+PEfNrhsbgVWdh9uPiGEEEIIIYQQQoj/kHLlyrFixQr12s/PD4PBgL29fbrjdu/ezZw5czh9+rRarxkgV65cREdHq9cREREEBQWRM2dO5s+fj6OjI+3btwfA1NQUrVb7gXeUPgkuC/EO4uPjSUxMZNmyZWTKlLImsbu7O/Hx8epvkV73trIYbypbtizXrl3j1q1buLq6cvr0aQCuXr1K27Zt1X7FixfH39+fqKioDO/HYDBgMBjU67CwsAzPIYQQQgghhBBCCCGMVa9enbCwMDw8POjSpQtTp06ldu3aaLVaQkJCsLa2ThEAvnHjBu3atWPx4sXkzp2biIgITExMsLS0pF27drRr147atWtToEABfvrpJwoXLkzJkiV5+PAhP/zwA9mzZydHjhz8/PPPtGvX7qPu1+SjPk2If6i1a9dia2uLs7MzDg4O2NnZsXDhQnbu3ImdnR05cuTA2dkZjUbDjRs31HFxcXEZflbJkiW5du0avr6+lCxZUm0PDg7G1tZWvU7+OiQkJMPPmDZtGra2turr9VIeQgghhBBCCCGEEOL96HQ6Vq5cSd++fcmSJQu7du1ixowZAGTOnJmrV6+mGLN8+XIiIyPp1KkT1tbWWFtbU7RoUQDq1KnDjBkz6NWrF4ULF+bOnTts27YNjUZD48aNGTlyJB06dKBq1ao0aNCAYcOGfdz9ftSnCfEP1bVrV9q0aYOpqWmqNZIhKbs5+QC/ZKGhoRl+VokSJdi/fz/Xrl0zCi6/SVGUDM+dbNSoUQwePFi9DgsLkwCzEEIIIYQQQgghxAfQpEkT7t27x4ULF6hYsSIODknnW6UVy5k7dy5z585Nc74ffviBH374IdV7gwcPNorxfGwSXBbiHYSEhKgnemakds2rV6+IiYlJtfwFJBVlf5O1tTV6vZ4///wTNzc3td3BwYHg4GD1OjQ0FI1Gk+ZJo6mV6EhmZmb2TocNCiGEEEIIIYQQQoiMc3JyomHDhp96GX87CS4L8Q7s7OyIjY1NM2sZ/pe5/Lrz589TuXJljh8/nuqYtILOJUqUYNeuXfz6669qW8mSJbl8+bJ6ffXqVfLly4eFhQX29vZG5TFCQkLeWig+VTGREBny1m5CCPGf9eI57N4BwUHg+iV8XRfS+WUeADeuwR/7ITERateD4v//qZS1q+Ghf8r+YyfCgjkQGmLcbmsH/T5dRoIQQgghhBDiNTERn3oFnwUJLgvxDuLi4jAxyXiJ8nXr1tG4ceMMjytZsiQ+Pj5GNZY7depE7dq1adq0KV988QVTpkyhY8eOANSsWZM5c+bQpEkTLC0tWbBgATVr1szwc3lwGfTyY0EIIVKVkAgH/4RsDlCjDFy+CfuDIW+OtMeERsCRM+BaGOxt4Y/fISoArK2gdF4oled/fR8/T3rdOA41XOH1j8zdfgAxhqR7QgghhBBCiM+CuakpWaxt397xX0yiSEK8g9GjRzN//nzMzc3fOci8bds2rl69yq5du1Lcu3r1KhEREbx69SrV8hSlSpVKUW+5SpUquLu7079/f8LCwmjbti2jR48GoGfPnty+fZsGDRoQFxdH/fr1GTduXIb3eWziHDJZZ8rwOCGE+C84evAPJh69wN7de7GwsOD2jRtMHz+B1TMXpzlm1qQp+FfRs9BzFQAbPdYQEhRE7yGDjPolJibSuv43jFu0hFJfljG6FxkRQYs69fHYuokcuXJ9+I0JIYQQQggh3ksWa1ucHbN+6mV8Uhrlr5wKJsQn8OjRI+Lj43FxcXnnMXv37kWv11OnTp2/bV3JZTGuX79Onjx5+PLLL+nbty99+vRJ0bdVq1bs3buXr776il27dmWojvOWLVt49eoVvXr1+mBrDwsLw9bWltDQUGxsbD7YvEII8W8yYcIEzpw5w969e4GkwzgcHBwICgpKc0ytWrVo0KABw4cPB8Db25uJEyeyb98+o35bt25l6dKlHD58OMUcP//8Mzdv3mTVqlUfcDdCCCGEEEIIkbZ3jRVJ5rL4xxk5ciTBwcHqP+7fxYMHD1i+fDk+Pj5p9omIiMDa2pqcOXOi06X+V+PZs2fMmzePnj17GrWvWrWKHDlyoCgK0dHRmJqa4uPjg7m5earz/PLLL+j1eqpVq8b+/ftp2LAhsbGxAJiamqr9FEXBYDAYzWNtbU2HDh0oUaIEVatWxdTUlLi4uBTPWLhwYaqB7fRc8rsnmctCCPH/3sxCCAsLM/rFpkajQavVEhwcnObhqm+OsbGx4cmTJyn6LViwgIEDB6ZoT0xMZPHixWzfvv0v7EQIIYQQQggh/h4SXBafNUdHR4KCgtCkcljS6wFgRVFwcXHh7t27qc7z3Xffcf78eSIiIsiUKfXgaXJQ9+TJk2ketJcczH1dVFQUEydOZPPmzQBUqFCBhw8fotVqsba2JiEhgadPn/L8+XMcHBwA1IP/LCwssLS0BGDatGlMmzbNKJAcGxtLTEwMiYmJaluDBg349ttv2b59u7qeY8eOUaJECaM+6R0+mJYa4wZLzWUhhPh/5qam3JrvoQaYdTpdilJG5ubmREVFpRlcfnNMcv/XXbt2jbt379K0adMU4/fv34+joyNlypRJcU8IIYQQQgghPjWJIonPmqmpKYcPH6ZmzZr4+PgwdOhQ1qxZQ643ak56eXnRu3dv9XrevHkMHTo0xXxr1qwxul68eDE//vgjgBrArlq1arqZy926dTNqGzduHJ07d6Zs2bIMGzaMI0eOsHDhQhwdHenTpw+HDx9m0qRJamAZ4P79+yQkJGAwGHj69CnXr19nzJgxjB8//p3el/nz56sfSdBqtVhYWBgFzbVa7XsdQEieUmDr8PZ+QgjxbxcTQYzfRQLDQ9Xgsr29Pb6+vkbdwsPDU/zS8XX29va8fPky3f6//PILLVq0SLVE0saNG/n222//yk6EEEIIIYQQ4m8jwWXxWWvRogVOTk68fPmSNm3a8ODBA6pWrWrUp3379nTt2pV27dqpbVqtlo4dO+Lp6Znm3K6urimyn+HtmcuvZxEvXbqUzZs3M23aNHr37s21a9fInDkzcXFxagbynj17UmSjrVmzhoCAAI4fP46dnR0HDx5k/vz52NqmfsJo8jOjo6OxsrIiS5Ys6r3Usrrfm7kVWNl9uPmEEOJfpFy5cqxYsUK99vPzw2AwYG9vn+4Yb29vfvjhBwB8fHzImTOnUZ8tW7awdOnSFGMNBgO//fYbEydO/EA7EEIIIYQQQogP6z1SG4X4eBYsWEBUVBSVKlUiMDCQpUuX4u/vj7+/Pz179sTa2ppRo0ZRoEABfvrpJ3Xcux6Q93p2b3x8PHny5KFmzZrkzZs31dfjx4+NPt6cJ08eevfuzZ07d9iyZQvr169Hq9USFxeHwWAA4Pfff2fGjBkUKFBA/Sj0hAkT1LrN3bt3Z9q0aTg4OGBtbY2dnR3m5ubq15aWlnTs2JGnT5+SI0cObG1tyZr1fzVA3+dMToPBQFhYmNFLCCFE+qpXr05YWBgeHh4ATJ06ldq1a6PVagkJCSEhISHFmJYtW7Jp0yauXr1KREQE7u7u1KtXT71///59Hjx4QOXKlVOMPXXqFHZ2duTLl+/v25QQQgghhBBC/AWSuSw+a3FxcYwYMYKBAwfSsmVLvvvuO3755Rdy5cqFr68vhw8fxtra+oM8y9LSklOnTuHg4KBmHXt5eeHs7JzmP+wbNGhArVq1qFq1KqtWrVIPbQoKCuLIkSP07t2b27dv4+PjQ/fu3dX6ygA7duwAoH///vTt25fY2Fg12F27dm0GDhxIo0aNjJ4XGhrK+fPnadGihdqWWjADMMqwftO0adOYMGHC294SIYQQr9HpdKxcuZJ27doxbNgwTExM8PLyAiBz5sz4+Pjg6upqNKZUqVIMGDCAsmXLYm5uTsGCBY3KOB09epTSpUunegDs0aNHUw06CyGEEEIIIcTnQjKXxWdNr9dz8OBB+vbtS2RkJBUqVODkyZP88ssvODg4sH//fvz8/FJk74aEhLB27Vp0Ol2ar8uXLxsFZhMSEmjUqBHdu3dX20aMGMGhQ4eApAzhhIQEYmNj1fsxMTG0bduWPHnyoNVq2bRpE5D0Uenw8HD1kL/ff/+dWrVqqeMiIyPx8PDAxcWFXr16MWnSJIKDg1m7di2RkZFqv/379/P8+fMU78vrGdempqbUrFkTOzs79XXhwoV039dRo0YRGhqqvh49epRufyGEEEmaNGnCvXv3WLNmDTdu3KBo0aJA0v8j3gwsJ5syZQo+Pj5s27aNP//8EwsLC/XeDz/8wOnTp1MdN2nSJPX/K0IIIYQQQgjxOZLMZfHZunr1Kr/++is3btzg/PnzWFpa0qpVK+7evYulpSVbtmzhl19+UTPAsmfPzu7duylcuDAvXryge/fuLFu2LM35Z82aRcGCBdXriRMncu3aNfz8/LCzswMgIiKCq1evMmzYMBRFITExkaJFi3L27FkAdu7cyb59+yhZsiS//fYbtWvXJjo6mnv37rFjxw6aN29O3bp1WbFiBTt37lSfNX78eCpXrkxERATlypVj3bp13Lt3j549e1K/fn2137x587Czs0s1uJCYmEhcXBxBQUEoiqLWXk5ISHhrWRAzMzOj8h5CCCHenZOTEw0bNszQmKJFi6qBaCGEEEIIIYT4t5DgsvhsaTQaTpw4QfPmzdHr9Zw4cYLVq1ezevVqo352dnZMmzaN4OBgChcuDMCZM2f47rvv0p1/6NCh6tfLly9n1qxZHDt2jEqVKqntVatWpVu3bnTu3Flte73cRKtWrWjRogUmJiZcvHiRhw8fsmHDBpo3b07p0qVp3LgxFStWpFChQpQuXRqA8PBwDhw4wIEDB+jatSsAjRo1ok+fPnTs2NGonvKiRYsoVqwYf/zxB3Xq1DFa/4gRI8iePTt9+vShevXqLF68mC+//JJvvvmGTp060b59+3d5m43FREJkSMbHCSE+Ly+ew+4dEBwErl/C13XhbYd/3rgGf+yHxESoXQ+Kl0xqVxSYNQ0MMf/rW+MrqFYT1q6Gh/4p5xr7LziALibiU69ACCGEEEIIIT57ElwWn63ixYurJSlu3LhB586dcXNzS9HPycmJatWqkTdvXgDu3LnDuXPn2Lhx4zs/q169evz+++88fPiQJk2aYG5ujomJCc+fP+fmzZuMHz+e+Ph4DAYD7u7uauB2586dLFy4EF9fX0qUKEHdunXx8PDg+PHjAHz99dcsXLiQVq1aqc+ytrbGx8cHne5/f/3u3buHh4cH58+fN1pX/vz5+f7775kxY4YaXE5MTOTRo0d4eHhw5MgRxowZg6IolChRAoBmzZrRtWtXXFxcjALl7+TBZdDLjwUh/tESEuHgn5DNAWqUgcs3YX8w5M2R9pjQCDhyBlwLg70t/PE7RAWAtRWER4IWaFzjf/21wI3jUDovlMrzv/bHz5NeN47/TZv7uMxNTclibfuplyGEEEIIIYQQny2JIol/hDdrKr8puXayoigMGjSIFi1aqIfrvYts2bKRJUsWrKysaNOmjdqeVuZydHQ0FhYWFC9enP79+1OvXj2eP39O06ZNmThxIpkzZ2bKlCksW7aMbdu2MWbMGJ48ecK0adNwcnJSA8txcXHEx8cDMGPGDBwcHNi2bRt37txRa3JOmTIFKysr9fk7d+7E3Nyc/fv3c/PmTTw9PTl37hympqYA9OrVi3PnztGiRQsuXrxI9uzZ3/l9ODZxDpmsM71zfyHE5+fowT+YePQCe3fvxcLCgts3bjB9/ARWz1yc5phZk6bgX0XPQs9VAGz0WENIUBC9hwxi767fOGlqz9R5c9N9bmJiIq3rf8O4RUso9WWZD7qnTyWLtS3Ojlnf3lEIIYQQQggh/qM0ytuiduI/5/X6vcl2795NwYIF1bITqYmOjqZPnz6MHTuWfPnyAUkZx56ensyYMeMvremHH35g9+7dRiUjkt26dYuzZ89SunRp9u7dS+vWrbl8+TIFChR45/kXLlxI//79sbKyMqpFnJCQgImJidH7ER0dTd68ebl27ZrRHD4+Ply7do2tW7dy5swZGjZsyMyZM3FwcCAwMJCuXbuSJUsWo7IeLi4utG3blmnTpgHw9OlTvvjiCxo1asTq1auNDn1KdunSJe7du0fZsmUpVqwYO3fupHbt2kZ9IiMjKVu2LBMnTqR169Zv3X9YWBi2traEhoZiY2Pzbm+aEOKzNGHCBM6cOcPevXuBpJ/pDg4OBAUFpTmmVq1aNGjQgOHDhwPg7e3NxIkT2bdvHwMGDGDPnj28evUKU1NTfvzxRyZNmpTi/xNbt25l6dKlHD58+O/bnBBCCCGEEEKIj+JdY0WSufwvVrlyZa5evfrWg9uio6OpW7cuO3bsAJIOtouOjmb69OlAUoC1a9eurFixIt3g8qFDh9i7dy+LFi1S2/Lly8fvv//OmDFj0vyDuHLlSvr3759q4DgwMJDJkyezePFilixZombnJjtx4gRjx46lZMmk2qDffPMNVatW5cCBA28NLkdHRzN06FAWLVpEz549MTExYcSIEWrZi/HjxzN//nysra2BpMDvr7/+anSIU3LGtFarpXTp0uTNm5cuXbpw/Phxo5IUWbJk4ddffyU2NlZtS0xMJDIyknLlyqlt2bNnp1u3bpQrVy7VwDIklQspXbo0uXPnxtbWlm7duqn3YmJicHJy4tKlS1y8eDHNOdJyye+eZC4L8Q+SWmZtWFiY0Sc3NBoNWq2W4OBgMmfOnOo8b46xsbHhyZMnANy+fZvGjRszYMAA7t27R9u2bSlevDht27Y1mmPBggUMHDjwA+1MCCGEEEIIIcQ/gQSX/8VsbGxYsGCBWtIhISGBxMRE9Ho9APHx8Wi1WmbPns3ly5fVcZs3b2b+/Pnq9YEDBwgMDGTgwIFq4MDExIRDhw6pGcoA69ev58cff2TkyJFs3boVrVarZv2WKFECRVFISEggISGBZ8+eqePMzMyoW7cuO3fuTLGHzp07Y2pqahQgVxSF2NhYzMzMqFSpEoqicOvWLYoWLcrdu3e5ePEi69evR1EU4uLi0Ov1KTLsIClbuWXLlgDodDp69+5Nzpw5adu2LcWKFUNRFEaMGMGoUaMAqFixYopg7fr16+nVqxcWFhZoNBqio6MBaNy4sVG/xMREoqKi2LBhg/rMAwcOYGlpSdasWcmePTtarRatVgvAjh07GDVqFImJicTHxzNv3jy1XIdOp0Or1XLlyhXs7OyMnuPl5aVmHmY0sAxQY9xgqbksxD+Iuakpt+Z7GAWYdTpdil8qmpubExUVlWZw+c0xyf0B9u3bp7a7uLjQv39/tm3bZhRcvnbtGnfv3qVp06YfZF9CCCGEEEIIIf4ZJIr0L6bT6QgLC2PBggX069ePs2fP0qZNG27duoWFhQWHDx9m8uTJNG3aVA1qHjhwACcnJ2rXrk3//v0ZP348EydOxNzcnNOnT+Pk5MSwYcMICAgwCiw/fPiQ7du34+npSbt27YyC029KzvZ9fZ3pebNyi7+/P+XLl8fCwgITExMgKUs7MTERe3t7rKysKFeuHImJicTGxnLlypUUWdHh4eGcO3eOYcOGAUllJOLj42natCm+vr7kz58fd3d3qlSpYjQu+XnJOnXqRKdOnYCk+sklS5akXbt2jBs3Lt09AcydO5cCBQpQpUoVnjx5kmoAPHn/b74Hyd+vtPq/tzylwNbh/ccLIT6emAhi/C4SGB5qFFy2t7fH19fXqGt4eHiKT368zt7enpcvX75T/6xZsxIQEGDU9ssvv9CiRYt0fzYJIYQQQgghhPj3keDyv5ylpSXLly8na9as3L9/n0aNGtG8eXPGjRuHl5cXrq6uat+IiAgGDx7M6tWr+f3339mzZw92dnbodDqGDx/OuHHj6Nu3L2vWrOHixYtGz5kwYYL6tVarpU6dOjx48AAzMzO0Wi2KohAfH09kZCR79uyhePHiav+YmBgOHjxI3rx5U6w/MDCQUqVKGbW5uLiomc/JgYzvv/8eV1dXBg8eDKBmLZuYmKQavJ47d67Rx7dnz57N1q1b2bdvH/nz5yc6OppDhw4xevRotY9Go+HJkyckJCSgKEqKed3d3bl9+zZdu3ZN7Vth5MSJExw5coSaNWui0WhYvnw506dPx8LCAp1Oh0ajISEhgZiYGNq2bcukSZPUsYmJiWog+81gd0xMDNmyZXvr89NkbgVWdu8/XgjxyZUrV44VK1ao135+fhgMBuzt7dMd4+3tzQ8//AAk1ZDPmTMn0dHRlC9fnrNnz6qfhvD29iZPnjxG47ds2cLSpUv/ht0IIYQQQgghhPicyYF+/2KNGjWiVatWuLq60rx5cxwdHZk3bx5Xr15l48aNhIeHs2TJEk6cOIGvry9FixZlzJgxFC1alMePH7Nq1Sri4+NxdXUlZ86cFClShJiYGJYuXUqzZs3U55w6dYomTZpQrVo1WrVqRceOHf/2vf3yyy8MGjQIc3NzAB48eEDu3LnVYGtyMHv48OEMGDDAaGxwcDB9+vRh48aNalt0dDTdunXj2LFj7N+/nyFDhpAzZ06jw/emTJnCnDlzSEhIwMPDg+bNm6v3zp49S/Xq1bG2tsbKyirFeh88eICfnx958+bFYDBQrlw5ypQpw+PHjzl06NAHfW/ehcFgwGAwqNdhYWHkzp0bho0Ge6ePvh4hxHuIDIEbx7kwczFl8hVUm+Pj48mRIwczZsygS5cudO/enWfPnrF7925CQkKwtrZOkWF8+fJlqlSpgre3Ny4uLlSrVo2OHTsyZMgQateuTe7cuenTpw8nTpxg+PDhHDp0iBo1agBw//59ihQpQmhoqPozWQghhBBCCCHEP5sc6CdUrq6u1KtXj/3791O5cmUqVqzI/PnziYuLo0KFCpw4cQKALl260LJlS3x9fXF3d1cDyBERESxatAiDwYBWq+X3338nf/78lChRAoBHjx4xbtw4fHx81GfWrFmTe/fuodfrMTExUestR0VFcejQIUqWLEn37t359ddfyZQpk1qTOPnwvDdFRUXRrFkzli9fTmxsLG3btqVdu3ZAUhZwp06duHfvXorSEsk1i1/PMv75558ZOnSoUT8LCwvWrVvHkiVLKFy4MHXr1qV79+5GfcaMGcOYMWNSrO3mzZs0a9YMg8HAypUrUw2uazQatZ5paGgoBQoU4LvvvmPatGkALFmyhIkTJ6qZ3hqNhsTERAwGA99//z3Tpk3j+PHjNGrUCBsbG3Q6HeHh4VhaWqb6MfS4uDhCQ0OJiIhI9f2cNm2aUba5EOLfQ6fTsXLlStq1a8ewYcMwMTHBy8sLgMyZM+Pj42P0qRWAUqVKMWDAAMqWLYu5uTkFCxakd+/eAKxevZrOnTtTtWpV8ubNy6ZNm9TAMsDRo0cpXbq0BJaFEEIIIYQQ4j9Igsv/EdHR0Tx//py7d+9SoEAB8uXLx71794zqHzs6OmJlZUWjRo3Ytm0bAN26dWPLli00btyYc+fOYWNjw9SpU6latSqZM2fmyJEj6qFOyQcHAmogIz0rVqxQP7r9yy+/sGLFCo4cOfLWcd9++y0XLlxQg6oPHjwge/bsuLi4pOibkJDAgAED1GDy8+fPCQgIoEyZMin6mpiY8MMPP6DRaChatCg5c+bE0tISR0dHICnI/uLFCwICAtRDsU6ePEmrVq2oV68et27dYtCgQYwdOzbVdScHvrNmzcqvv/5q9B716tWLXr16pbvv6tWrExYWBiQFj5ODRM7OzumOS82oUaPUEiLwWuayEOJfoUmTJty7d48LFy5QsWJFHBySaqmn92GlKVOm0KFDBwICAqhRo4Zac9nZ2Tndn80//PCDWk5DCCGEEEIIIcR/iwSX/wN8fX05cuQIvXr1YtCgQfTr149r165hZWWFp6en2i8uLo6WLVtiMBiYMmUKISEh9OzZE41Gwx9//EHVqlXVvqVKlaJXr15Gh/q9btiwYRw9ejTVe8eOHUtROuLIkSNG86dn586d6tcLFy5k69atHDly5J0Okpo5cybDhw9P8/7q1as5f/48q1evxtPTk9mzZ/Pnn38C0K9fPzQajRpYTkhIUA9LHD16NNWqVWPu3LlpZi6n59ixYwwZMiTVe0OHDlUD+MnOnj2Lvb39ewWWAczMzNRMaiHEv5OTkxMNGzbM0JiiRYtStGjRv2lFQgghhBBCCCH+bSS4/C+nKAp9+vRh7NixtG7dmqNHj9KlSxfc3d2Jj49n9OjR/PjjjwDo9XpcXFyoWLEixYoV44svvqBkyZJcu3aNzp074+bmBiRlJU+cOFEtS5Gax48f07dvX6NsZoBMmTKh1+tT9L969So7duxg8eLFRu1RUVHUr1+fX3/9NcWYTZs2MXv2bCwtLcmePTsWFhaEhoZiZ2dHQkICoaGh3LlzRz3g7vHjx4SGhlKsWLFU15yYmMj8+fNZsGABAC1atGDq1Kl4eHhQpkwZdu7caVT6Q6vVsnnzZqM50stcTk9MTAyZMmVKkfHdt29fNVv5defOnSMqKoosWbKk2ENwcDAhISHY2tpmeB3ERCbVcRVCfP5iUi97I4QQQgghhBBCfCwSXP6Xu3TpElZWVnTv3h0TExOePXvG119/TcuWLUlMTKRevXqsXLlS7b9o0SJu3brFiRMnmDhxIosWLUo16zb54LzXvf5x69Tup3fv9OnTqfbt1KkT+fPnN2qLiYlh1KhRbNu2jUOHDlGoUCEAAgMDcXR0JDAw0KjGcrJp06YxcuTINNe1du1aHBwcqFu3LpCUbbx9+3aqVq2KiYkJq1evThHMfVNGMpf/yvs1cOBABg4cmKL96NGj/PDDD+8XWAZ4cBn08mNBiE8mNAIuXIeIKMibE0oUgHQ++WBuasoZr+M0r1WbuLg4Zs+erf7iT1EUMmfOTGhoqNp/0qRJjB07loSEBPr27cuGDRuIj4+nQ4cOLFmyJNWfnUIIIYQQQgghRFrkX5H/YgkJCZQuXZr58+erbX369KFPnz4AxMfH4+fnh4+PD+bm5kRHR5M3b14A2rdvz8CBA9Vg6pw5c9QgtMFgoGTJkimeZzAYSExMBJIyaAcPHpwiizcqKkrtk5arV69iYmJCaGgo+/fvNyrdkZCQQI0aNYiNjeXkyZNvLQuRHMD18/NDURQKFCiQar+QkBBGjx7N0qVL1banT5+yYMECtFottra2zJ8/HysrKypXrpzqHK/Xr052//59bty4AZAiY/vN98vb25tcuXKlWNecOXPS3WNAQADBwcEoisKKFSsoV65cuv3Tc2ziHDJZZ3rv8UKI9xdriKVl3fpUqv8N33Xvxs8TJ1G7Qm2atGqZ5phXj5/QqE5dFi1aRIUKFWjRogVlypShUKFC3LlzBzs7O/z9/dX+FhYWAEyfPh0fHx9Onz5NbGwsdevWpXz58ikOMhVCCCGEEEIIIdIjweV/sdez1VKj1+vp3r07iqIwY8YMLCws2LdvHyVLljTKXouOjmbw4MFGZTFSK/3w6tUr4uLigKTA6Zw5c1ItixETE6MeFJWa8ePHs3v3bnLkyEGDBg2oXbu2ek+r1bJixQry58/PvHnzmDRpEubm5up9KysrNSCuKArR0dEcPXqUwoULM378+DSfuX37duzt7WncuDG+vr60b98ef39/OnfuzKVLl7C2tmbu3Lk0atQIR0dHNm/ejKurq9EcMTExKeb19fWlY8eOdOnSRT1Q6/X3KyYmhlevXmEwGKhUqVKqZTFSm/d1Fy5coGnTptjb21OkSBG1rMf7cHXJj42NzXuPF0K8v507dxIdGcnalauwtLQkr30W+vTpg9vwtD9xMdB9EbVq1aJbt25A0s+MdevWMXnyZM6dO0elSpWws7NLMS4wMJCNGzeqdfMbNGhgVPZHCCGEEEIIIYR4FxolvaPjhQC15u/HCjrGxcWh0+neegjeh/bq1Ss1APzLL7/QuHFjMmUyzuKNiIjgt99+o127du+0PkVR0u03d+5c/vzzT7Zu3WrUfvLkSb777jv8/PyM2pcvX07Pnj2NSmVkzpyZJ0+eGGVGt2jRgnr16tGjR4+3rhGSvse2trYcu3RRMpeF+EiyWNvi7JhVvZ4wYQJnzpxh7969QNLPDwcHB4KCgtKco1atWjRo0EA9qNTb25uJEyeyb98+BgwYwJ49e3j16hWmpqb8+OOPTJo0KdWfSRUrVqRNmzYMGjToA+9SCCGEEEIIIcQ/UXKsKDQ0NN2YoGQui7f62JmsqR349zG8nlmc1mGFmTJlon379u8859sC0GZmZkaZ1x06dKBly5bkyZNH/fj663Q6Hd9++y2bNm0C4O7du9SoUQO9Xs/OnTuZOnUqZ8+exdTUFDMzs3deZ7Ia4wZLzWUhPhJzU1NuzfdQA8xhYWG4uLio9zUaDVqtluDgYDJnzpzqHG+OsbGx4cmTJwDcvn2bxo0bM2DAAO7du0fbtm0pXrw4bdu2NZrj6NGj+Pr6snv37g+9RSGEEEIIIYQQ/3ISRRLiE4mOjsbExITo6GjWr19Px44dOXPmDIMGDUKr1arZyQkJCcTHx2NmZpZqsDq5zczMLNWAdIbkKQW2Dm/vJ4T4a2IiiPG7SGB4qBpc1ul0KX4pZG5uTlRUVJrB5TfHJPcH2Ldvn9ru4uJC//792bZtm1FwOTIyku7duzN+/HgcHR0/2PaEEEIIIYQQQvw3SHBZiE8kR44c/PTTT+j1egYPHkz58uV58OAB9evXJyEhgfDwcLJkyUJCQgIdO3ZkwYIFxMfHs3v3bvXgxfj4eLXOtUaj+eulRMytwMrur80hhHgv9vb2+Pr6GrWFh4enW6Pe3t6ely9fvlP/rFmzEhAQYNTWt29fnJ2dGTJkyF9YuRBCCCGEEEKI/yqTt3cRQnxoL1++xNLSEktLS8zMzGjRogVTpkyhVq1aBAYGqocQBgYGEhwcrB7S1759e27dukXz5s357rvvOH369HsdwmUwGAgLCzN6CSE+rXLlyuHt7a1e+/n5YTAYsLe3f+cxPj4+5MyZk+joaEqUKEF0dLR6z9vbmzx58qjXixcv5uDBg/zyyy9GddyFEEIIIYQQQoh3Jf+aFOIT8PHxoUiRIur14sWLef78Od9++22aYxISEoiLiyNLliwYDAYAsmTJgr29vZq9/K6mTZuGra2t+sqdO/f7bUQI8cFUr16dsLAwPDw8AJg6dSq1a9dGq9USEhJCQkJCijEtW7Zk06ZNXL16lYiICNzd3alXrx4WFhZky5aN3r17c/78eebOncvGjRvp1asXkFRnefDgwaxZswYrKysiIiKMAtFCCCGEEEIIIcS7kOCyEJ+Avb09P/zwg3ptYmLC2LFjadKkSYoAUmxsLHFxcdy4cYMsWbKQJUsWli9fzs8//0yWLFmws7Ojd+/eGXr+qFGjCA0NVV+PHj36IPsSQrw/nU7HypUr6du3L1myZGHXrl3MmDEDgMyZM3P16tUUY0qVKsWAAQMoW7YsOXPmRKvVqj8PVq9ezYMHD6hatSrLli1j06ZN1KhRAwB3d3cMBgN16tTB2toaa2trGjRo8PE2K4QQQgghhBDiX0FqLgvxCZQtW5ayZcuydOlSta1q1ap89dVXapmL5JrLBoOBOXPm0L17d+Lj4wGoVKkSI0eOpGnTpixZsoTr16+TmJiYamZjaszMzFIcHCaE+PSaNGnCvXv3uHDhAhUrVsTBIemATUVR0hwzZcoUOnToQEBAADVq1FBrLjs7O3PkyJFUx+zYsePDL14IIYQQQgghxH+OBJeF+IwkB4IuXbpEx44dUxzuBRAYGMjVq1cpU6YMAFFRUZibm2MwGIiJifmo6xVCfHhOTk40bNgwQ2OKFi1K0aJF/6YVCSGEEEIIIYQQqZPgshD/IIqiMGTIEKpVq6bWSY6Ojsbc3JymTZtmOCCVQkwkRIb89YUK8am9eA67d0BwELh+CV/XBY0m/TE3rsEf+yExEWrXg+IlU/YJDoJli2DkT8bt3ifh5Qto0uLd1hcT8W79hBBCCCGEEEKIz5gEl4X4hOLj49VSFwaDAZ1Oh1arNeqjKAqxsbHExMTQp08fDh06xJ9//klISAj79+9nz549dOzYERMTE4KDg7lx4waXL1+mRYt3DHK97sFl0MuPBfEPl5AIB/+EbA5Qowxcvgn7gyFvjrTHhEbAkTPgWhjsbeGP3yEqAKytjPuduAjxcXDj+P/a/J/AxRvg7GTc/hbmpqZksbbN4OaEEEIIIYQQQojPh0SRhHiL69evc/HiRTp27AjAmjVrCAkJYcCAAX957ri4OLWUxTfffMOVK1cwNTVF8/8Zlrly5UJRFAwGA4sWLeLixYucOHGCfPnyYTAYmD59OpUqVeL7778H4OnTpzRu3JgqVarw1VdfZXg9xybOIZN1pr+8LyE+paMH/2Di0Qvs3b0XCwsLbt+4wfTxE1g9c3GaY2ZNmoJ/FT0LPVcBsNFjDSFBQfQeMkjt8/uOnXhc9sPvRRAX/n+u86fPMGfqNIp+25q4uDgmzJzxzuvMYm2Ls2PW99ylEEIIIYQQQgjx6WmU9E4JEuI/ZuXKlQwbNoycOXPi5+fHgQMHcHJyonz58ty4cYNs2bLRvn17vvjiC9zc3ADIkSMHkZGR6PX6dOeOjIykZ8+ezJ07F0gKWr9ZI7V27dpUqlSJSZMmpTpHbGws06dPZ8SIEfTq1YuSJUtSrVo1fHx86NatG5UqVWLRokVqPeZ3FRYWhq2tLccuXZTgsvhHSS1AO2HCBM6cOcPevXuBpOx/BwcHgoKC0pynVq1aNGjQgOHDhwPg7e3NxIkT2bdvHwCvXr2iWLFi/Prrr1SpUkU9YO/p06fY29szbdo0/P398fT0/Bt2KYQQQgghhBBCfFzJsaLQ0FBsbGzS7CeZy0K8xsLCgqZNm+Lp6UnNmjWxtramQIEC1KlThxMnTtCiRQuOHTvGnDlz1DE2NjZs3LiRmjVrAknlLfR6PSYmJkBSQNjU1JS+ffuSKVMmtU+9evUYNWoUvXv3BuDFixecO3eOTZs2pbk+U1NTXrx4wahRo9DpdJiamrJw4UJq1arFy5cvuXjxIgULFnzv/dcYN1jKYoh/FHNTU27N9zAKMIeFheHi4qJeazQatFotwcHBZM6cOdV53hxjY2PDkydP1OvBgwfTpk0bKleubDQue/bsH2orQgghhBBCCCHEP45EkYR4zZv1jrVaLUePHqVdu3bodDoWLVqElZUV58+fp3jx4uTNmxedTsfTp09ZuXIl3bp149dff2Xu3LmcOXMGjUaDh4cHJ06cwM7OTp3fzMyMTZs2UbduXcqWLUv58uXx8PAgMjKSAgUKGK1Bo9Fw9epVcuXKxaNHjyhfvjzBwcEcPHgQvV5PQkICWq2Ww4cPU758eaytrYGkes6Korw1o9pInlJg6/DX3kQhPpaYCGL8LhIYHmoUXNbpdJiZmRl1NTc3JyoqKs3g8ptjkvsDHD58mBMnTnD16tW/YRNCCCGEEEIIIcQ/lwSXhXiLvn37otfrMTc3B8De3p4uXbowdepUunfvDoCVlRWjRo2iRIkSeHl50ahRIypUqMCWLVvw8vKibNmy+Pn5Gc1bpUoVhg8fzogRI/j999+ZO3cuf/75J+XLl1f7bN26lcmTJ5MrVy4Anj17xpEjR7hx4wZnz56lWrVqFC5cmIMHD5KYmMiNGzfImzcvoaGhKIrCnDlz6Nq167tv1twKrOz+2hsmxCdmb2+Pr6+vUVt4eDimpqbpjnn58mWK/jExMfTs2ZNly5ZhZWWV5nghhBBCCCGEEOK/yORTL0CIz82uXbsoXrw4586dA5IyGjdt2sTp06fVV7169Ywygm1sbFi4cCH9+vXj4MGDdO3ala+//pqxY8dy5MgR2rVrl+qzRo4cya+//sq4ceOoVq0a5cuXZ+rUqUydOhWA3377jcaNG6v9y5UrR9euXQkKCqJWrVoUKlSIsLAwFixYwM6dO9m0aRP+/v78+OOPjB07Ns3AssFgICwszOglxL9FuXLl8Pb2Vq/9/PwwGAzY29u/8xgfHx9y5szJmTNnuHfvHq1bt8bOzg47OzsA7OzsOHny5N+2ByGEEEIIIYQQ4p9AgstCvKFp06b4+vpSrlw5ANI68zIxMdHoulGjRtjb2+Ps7EyuXLkYPXo0Bw4coESJEuTIkSPVOczMzLC1taVmzZrMmjULgCdPnhAcHAxAkyZNjALEnp6e9OrVSw2Aly5dmuzZs9OjRw+ioqK4d++eOkdazwSYNm0atra26it37tzv+O4I8fmrXr06YWFheHh4ADB16lRq166NVqslJCSEhISEFGNatmzJpk2buHr1KhEREbi7u1OvXj0qVKjA/fv3uXTpkvoCuHTpEmXLlv2Y2xJCCCGEEEIIIT47UhZDiLcwMTHhu+++Q6vVotfriYuL4+nTp9SoUSNF3+joaG7cuEFQUBB2dnZkz55dPdgvNbdv36Zt27acOXNGzYR+/PgxWbMm1Y9t3bq1Uf/WrVvTokULrly5wrlz55g7dy5arZYffviBoUOHcurUKXr06MH9+/f54osv0nzuqFGjGDx4sHodFhYmAWbxr6HT6Vi5ciXt2rVj2LBhmJiY4OXlBUDmzJnx8fHB1dXVaEypUqUYMGAAZcuWxdzcnIIFC9K7d2/Mzc3Jmzdvimek1iaEEEIIIYQQQvzXSHBZiNeEhISwfft2vLy8ePbsGZCUobh582Y2btzIoEGDmDx5Mg8ePEgxdt++fYSFhVG7dm3Gjx9PyZIlsbCw4NKlSxw+fDjV502aNIny5curgeX4+HhOnjxJpkyZ1IP6Xrdo0SLmz59PUFAQNjY25M+fnxcvXuDm5kbPnj0pUqQIISEh3Lp1i1KlSqW5TzMzsxQHngnxb9KkSRPu3bvHhQsXqFixIg4OSQdVpvVJBIApU6bQoUMHAgICqFGjRpo1mlObw83N7YOsWwghhBBCCCGE+CeR4LIQr7lz5w7du3dnzpw51KxZU2338/MjX758aY6Ljo5m4MCBuLu7U7BgQS5cuED37t35448/OHLkCJMmTaJ48eJGYy5evMiBAwe4ceOG2ubp6UnZsmVxcHBg7ty5DB061GjM8OHD6datG2XKlOHSpUtYWFhQoEAB2rZti42NDdWqVaNly5ZUrVrVqCa0EP9FTk5ONGzYMENjihYtStGiRf+mFQkhhBBCCCGEEP8uElwW4jU3btygadOmKdq3bNnC2LFjjdouX75MyZIlAfDy8qJSpUrUq1cPgOXLl9OnTx/KlStHiRIl6N+/P8OGDVPHRkdH06VLF8aNG6dmVF64cIExY8awf/9+HBwc+PLLL7G3t09xKN/FixfJmjUrDRs2xNramlKlSuHs7AxAz549qVWrFjt37ny/NyAmEiJD3m+sEB9bTITRpa+vL126dOHu3bt069aNmTNnotFo0p1i27ZtDBkyhLi4OGbPnp3q4Zv379+nePHiREVFGbXPmjULX19fPD09//JWhBBCCCGEEEKIfyIJLgvx/8LCwvDy8mLevHn4+/vz4sULAFasWEFERASNGjXC29ubsLAwFEWhbdu2zJgxg4SEBBo0aGCU6Tx9+nT167i4OO7cucP169epVasWAAsWLCA+Pp6ePXsCsHbtWgYOHMiyZcsoXbo0AL/99ht16tThzJkzTJs2DXt7ewBq165NrVq1GDlyJIcOHcLe3p6ePXsyevRohg0bRo0aNRg9ejQVKlTAyckpY2/Cg8uglx8L4p/D3NSULNa2GAwGGjduTL169di0aRP9+/fH09OTLl26pDnW19eXDh06sGjRIipUqECLFi0oU6YMhQoVMurXs2dPoqOjjdo8PT0ZOXIkHTt2/Fv2JYQQQgghhBBC/BNIFEmI/3fy5EmqVKnCF198QYUKFdDpdJw6dYpRo0Zx8OBBTE1NKVSoEA8fPkSn0/HFF19Qu3ZtQkND051Xp9PRokULcuTIQZMmTQAYPHgwzZs3R6fT0aRJEy5cuMCOHTuMDgmsVKkSx48fp23btrRu3ZpDhw7x6NEjNmzYwPr16/nqq684ceIEOp2OqVOnUqFCBaZPn06nTp3o2bMnrq6ubNq0ySjo/TbHJs4hk3Wm93r/hPgUsljb4uyYlZ07dxIaGsqcOXOwtLRk6tSp9OnTJ93g8sqVK6lVqxbdunUDoG/fvqxbt47JkyerfdatW8fjx4+Nxnl5eeHu7k7Xrl2JjY39ezYmhBBCCCGEEEL8A0hwWYj/980331C7dm0Ajh49iqWlJc+fP6d06dKULVsWSKrhmnzQX7InT56kO6+FhQX+/v5GbTqdjoIFC5KQkMCsWbNwcnLCxsbGqE90dDTFihXj8uXLBAcHo9FosLOzIyEhAVdXV7p27UqmTJlQFAW9Xk/NmjXp1KkTAEuXLuWrr76iYsWKf+UtEeKzlRxUTnb58mUqVqyIpaUlACVLluT69evpznH58mUaNGigXpcvX56JEyeq169evWLYsGH8+uuvVKlSRW0vVKgQ3t7eTJs2LcXfbSGEEEIIIYQQ4r9EgstCvMbU1BRADVBly5aNbNmy/W3P69+/P66urjRr1owrV64wZswYNm3ahImJCb///jtLlizh8OHDWFhYAGBjY0PTpk2ZPHkys2bNAkCj0fDTTz9RpUoV7ty5Q8GCBQH49ttvM7yeGuMGS1kM8Y9gbmrKrfkeaoA5LCwMFxcX9b5Go0Gr1RIcHEzmzJlTnePNMTY2Nka/LBo8eDBt2rShcuXKRuOyZ8/+IbcihBBCCCGEEEL8Y0kUSYhPZMGCBVy8eJE5c+ZQqFAhNm3ahF6vZ8GCBTg7O+Pv769mUr9u/fr1fPvtt2zYsIHZs2ej0+kwMTFBo9Go/RMSEkhISODs2bPkzp373ReVpxTYOnyoLQrx94iJIMbvIoHhoWpwWafTYWZmZtTN3NycqKioNIPLb45J7g9w+PBhTpw4wdWrV/+mTQghhBBCCCGEEP98ElwW4hN49uwZGzZs4LfffuP8+fOYmppiYWGBiYkJZmZm6PV6vL29cXR0ZNasWRgMBnr16oWZmRkrVqxg8ODBDB48mKFDh6b5jMTERExMTDK2MHMrsLL7a5sT4hOwt7fH19fXqC08PFz9NEJaY16+fJmif0xMDD179mTZsmVYWVn9bWsWQgghhBBCCCH+6TIYeRJCfAhOTk6cPn2ay5cvM2LECKysrOjSpQvnz59n+fLlREZGcvHiRb755hs2bNhApkyZ0Ov1zJkzh7CwMABMTEzo0qULBQsWpESJEri6ulKqVCmKFy+Oi4sLBw4c+MS7FOLjKVeuHN7e3uq1n58fBoMBe3v7dx7j4+NDzpw5OXPmDPfu3aN169bY2dlhZ2cHgJ2dHSdPnvzb9iCEEEIIIYQQQvzTSOayEJ9IYmIiI0eOZOnSpbi6uqLX61EUhdjYWPbu3Uvt2rVp1aoV8+fPp02bNjx//pxZs2bRtm1bdQ4PD4/3erbBYMBgMKjXyQFrIf6pqlevTlhYGB4eHnTp0oWpU6dSu3ZttFotISEhWFtbo9Vqjca0bNmSKlWqMGDAAFxcXHB3d6djx45UqFCB+/fvG/V1cXHh0qVLODk5fcxtCSGEEEIIIYQQnzUJLgvxicyZM4eLFy+SK1cuatSooQaX4+LisLKyIiAgAIBXr15hY2PD7du36dGjh3rYIMB3333H0aNHMTU1VUtgJCQkEB0dzcqVK2nUqFGqz542bRoTJkz4+zcpxEei0+lYuXIl7dq1Y9iwYZiYmODl5QVA5syZ8fHxwdXV1WhMqVKlGDBgAGXLlsXc3JyCBQvSu3dvzM3NyZs3b4pnpNYmhBBCCCGEEEL8l2kURVE+9SKE+K+5cuUKTZo0wWAw8PTp0xT33d3dWbt2LX/++ScuLi5qoBnAzc0NnU7H2LFj3/v5qWUu586dG4aNBnvJzBSfucgQuHGcCzMXUyZfQaNbz54948KFC1SsWBEHh3c7nPL69esEBARQo0aNdGs0CyGEEEIIIYQQ/xVhYWHY2toSGhqKjY1Nmv0kc1mIT+CLL75g7dq1dO3aFUgKGK9ZswYTExN69erF0KFDOXHiBL/99hsFChRIc545c+awcePGVO/98ssvFCxYMNV7ZmZmmJmZ/fWNCPGZcXJyomHDhina7969S3h4OCVLlkxRHqNo0aIULVr0Yy1RCCGEEEIIIYT415DgshCfgLm5OdWrV1evQ0JCmDx5MtHR0URFRREVFUWtWrUYPnw4AwYMSHOely9f0qhRI9zc3Izaixcvznt9KCEmMikrVIhP6cVz2L0DgoPA9Uv4ui5oNP+7HxORYsi2bdsYMmQIcXFxzJ49m3bt2gFJtc3btGnDqVOn0Ov1WFpacuzYMbJmzUrNmjU5duxYirnkAz1CCCGEEEIIIcS7keCyEJ+BCxcu0KpVK65du8aqVat49uwZRYoUwc/Pj3Llyhn1fT3wlVxnOTXp3UvTg8uglx8L4hNKSISDf0I2B6hRBi7fhP3BkDeHUTdzU1OyWNsC4OvrS4cOHVi0aBEVKlSgRYsWlClThkKFCrF27VqePXvGgwcP0Gq11KlTh8WLF+Pm5saePXuIj49X59y8eTObN2/+qNsVQgghhBBCCCH+ySSKJMQHoCgKmtczKwFPT08aNmyIo6NjmuMSExM5fPgwjx49onTp0uzZs4f27duj0+mYOHEiCxcupEOHDsycOZPWrVsDSfWSkz/Wn5iYyJw5c5g7dy7W1tbqvM+fPycxMTHD+zg2cQ6ZrDNleJwQH8rRg38w8egF9u7ei4WFBbdv3GD6+AmsnrnYqF8Wa1ucHbMCsHLlSmrVqkW3bt0A6Nu3L+vWrWPy5Mlky5aNBQsWoNfrgaRD/F69egVApkz/+7OemJjIvHnzWLVq1cfYphBCCCGEEEII8a8gwWXx0QQEBJArVy7y5MmT4l5sbCyKohgdbhcXF4dWq31rBm5yEPW9MnVfe76ZmRmZM2d+6zxhYWH8/PPPRuUqGjZsSPfu3WnevDmQdGBfnz59qFu3brpzRUdHU6JECXbt2kVAQAAzZsygWrVqODo68ueff+Lo6IirqyuzZ8+mXr162NjY8OrVKzVQZjAYGDBgAJ6enixYsIBmzZoBSWUxYmJiMvw+uLrkT7dIuxB/t93PN1KlcmWqFCsJQGmXAvT+rnOKg/ted/nyZRo0aKBely9fnokTJwIYtfv7+7N161Y8PT1TzLF9+3Zy5MhB5cqVP9BOhBBCCCGEEEKIfz8JLouPJjkgevfuXXQ64z9658+fp2XLlkZtvXr1YuPGjej1ejUrOCoqivj4eDUAqigKBoOBjRs30qJFCwBKlizJ1atX1Xl++OEHVq5cCYCXlxc9evTg+fPntG7dmoULF2JmZoapqSlmZmZcvHiRvHnzAkmBXwsLC3We2NhYTE1NadSokVHG45MnTzh9+jRr165V29avX09CQoJRoCpnzpwcP34crVbLokWL6Nu3L1qtlhw5/vdxf61Wy6lTp9BoNOzatQuAhIQE1q1bp+55xYoVav85c+YA4OzsbPTe+fr6pvYteKtLfvckc1l8VK9nIEPSL29cXFzUa41Gg1arJTg4mMyZM6c6x5tjbGxsePLkiVGfcePGMX36dLp27crXX3+dYo4FCxYwcODAv7gbIYQQQgghhBDiv0WCy+KjSQ4QOzk5pbgXHx+PnZ2dUdvKlSvVoDDAwYMHad68OUuWLOGHH35I9RlRUVHcu3ePFy9eqMFsMzMzAF69ekWzZs2YOnUqdevWpU2bNsyZM4dRo0YBoNPpuHPnDqdPn6Zt27bMmzePCxcusG3bNgDGjx+vZjUnl6WA/wWlwsLCcHd3p0+fPixdupTChQtz6dIlFEWhYsWKdOrUSR1nampKjRo18PLyAqB79+4UK1Ys1eBWzZo1MTU1NWqzt7cnLCws1fcgmZOTE48fP063z5tqjBssNZfFR2Vuasqt+R5qgFmn06l/Z9U+5uZERUWlGVx+c0xy/9cNHz6cwoUL06dPHxo2bEjjxo3Ve9euXePu3bs0bdr0Q21LCCGEEEIIIYT4T5Aokvhokg/OevbsWaqZy8klHVIbN3XqVKZOnYrBYODrr79m2bJlaDQaOnXqZBRU8vHxoWTJkqnWOd68eTOFCxemd+/eAPTv35/58+erwWVICkQPGDCASpUq4eXlRcOGDSlbtixHjx7Fy8uLoUOHcvnyZbX/9evX2bhxI9euXcPNzY2HDx/SpUsX+vTpw5kzZ9i4caMaBE6uBwuQL18+6tevD8D8+fNZuXIlWbNmZd68eWofc3NzDh48SKtWrYyyMiEpUH/37l01y/pNO3fupH///qneS1eeUmDrkPFxQryPmAhi/C4SGB6qBpft7e1TZN6Hh4en+AXL6+zt7Xn58mW6/TNlykT79u25desWq1evNgou//LLL7Ro0cLol0ZCCCGEEEIIIYR4Owkui48mLi4OgFy5cqW4Fx8fnyKwoygKO3bs4KeffiI+Pp7NmzerAWhzc3Pc3NwYP348gwcPpnfv3lhZWXH27FkeP36Mo6MjcXFxtGvXjnnz5mFmZsbZs2cpXbq0On/lypUJCAgweqazszM//fQTffr04dKlS+zatQtvb29Gjx7N7du3adSoER4eHmr/oUOHEhoaSpUqVXj8+DEXL15k165d9OzZk5s3b1KrVi3MzMz4888/jWo5f/3111SrVo2RI0eyePFiqlSpwtatW8mePTuPHz+mZs2ajBgxAmdnZ/r27Zvi/XqXINh71aA2twIru4yPE+IDKVeunFHpFz8/PwwGA/b29umO8fb2Vj/R4OPjQ86cOQEYMWIE9evXp1atWkDSpwbe/PuzZcsWli5d+qG3IoQQQgghhBBC/Ou9/wloQmRAfHw8uXPnJjo6Gn9//xSvx48f8/DhQ7Xv0aNHKViwIP369aNnz574+vpSpUoVdb5OnTpx584d3NzcmD17Nq6ursTFxXHr1i2qVq3KyZMnOXDgAH/88Qdz584F4Pnz5zg4/C8rt2DBgowePTrFWnv16oW/vz/169fH3Nyc6dOns3z5cpo3b57i4/ru7u7cvn2b2rVrM3DgQPLkyUP//v15/vw5ixcvJlOmTMTHx7N+/XqjwwoBDh8+jJeXFzdu3KBr165UrFiRMWPGULVqVYYPH06XLl0+2Pv/JoPBQFhYmNFLiM9B9erVCQsLU3+JM3XqVGrXro1WqyUkJISEhIQUY1q2bMmmTZu4evUqERERuLu7U69ePQBy585Njx49OH/+PD4+PixbtozWrVurY+/fv8+DBw/kID8hhBBCCCGEEOI9SOay+Nu9evWK/PnzY2lpafRR9eSAZvJBdZAU9IyLi+Phw4e4ubnRunXrFAHdZDqdjh49etC+fXuuXLmCXq9PkX04btw43N3dGTlyJHFxcWo2b/ny5bl9+za2trY8ePDAaIyiKMTExHDu3DliY2NxdHTEzs4u1UzgAgUK4Ovry++//86lS5d4/vw57dq14+LFi/Tv35+bN28SEBDATz/9hLOzM5UrV+bIkSNotVoaNGhA/fr11axMR0dH3N3dMTc35+HDh5w4cYLSpUsbHR6YLDQ0lAIFCqT5niuKYnRQ4JumTZvGhAkT0rwvxKei0+lYuXIl7dq1Y9iwYZiYmKi1yTNnzoyPjw+urq5GY0qVKsWAAQMoW7Ys5ubmFCxYUC1/06dPHx4+fEj9+vUxMzNj6NChtGnTRh179OhRSpcujbm5+cfaohBCCCGEEEII8a+hURRF+dSLEP8d7u7ulCxZkpo1azJy5Ei1vEVaxowZw7Rp09Is8ZCQkMCjR49SLbUBsH//frp06cLTp09p1aoVOXLkwN3dnYCAAC5fvkz79u0JCQkBkmqy+vr6sm/fPg4cOEBgYCDNmzcnKCiIc+fO8eeff3L+/HmGDh1Kq1at6Ny5Mw8ePODrr7/GycmJLFmyULRoUfLnz8+GDRu4f/++0Vrq1KlDy5YtqV+/PkuXLuX69etcvnyZ27dvU7VqVTp37kyDBg04e/YsmzZtYu/evdy7d49s2bLRqlUr3N3dAQgJCSFz5sw8efKE7Nmzp7rvmzdvsnr1ambOnJnqfYPBgMFgUK/DwsLInTs3DBsN9ikPXBTibxEZAjeOc2HmYsrkK2h069mzZ1y4cIGKFSsafeIgPdevXycgIIAaNWqkW6NZCCGEEEIIIYQQ6QsLC8PW1pbQ0FCjxNA3Seay+Gji4uKYPHkya9euVdvmzZuHh4cHCQkJxMbG0rhxY1atWqXeNzMz49tvv2XTpk0p5ksOsr6e2VypUiW2bNmSFCgFvL29yZMnD5CU3bh3714AcubMmeLQMIAXL14wYcIEDh8+TFxcHFeuXGHSpElcuXKFadOmMX36dKP+5ubmVKxYkdKlS1OkSBGKFy+Os7MzW7ZswdPTk5o1awLg5uaGiYmJeohf8rN79uzJ0KFDOXfuHOfOnUuxnkaNGtGpUyejAwrPnDmDo6NjmoFlgMKFC6cZWIak9zWtjHAhPrW7d+8SHh5O/fr1M3TIXtGiRSlatOjfuDIhhBBCCCGEEEK8ToLL4qNZv349r169ws3NjZIlSwIwcODAdDOX3+VQOo1Go35drFgxevTowfjx47l58yazZ89m0aJFAHz//fdMmzaNOXPm0Lx5c2bPnp1irt9++42uXbtSrFgxFEVh5syZ/Pzzzzg7OzNz5kzMzc1p3ry52j9btmysXr2ay5cvc+TIEbZu3YqHh4fRmlLby8KFCwEIDAzkyZMnpPYBgqVLl3L69GlatGhh1L5u3ToaNmz41vflvcREJmWTCvGuXjyH3TsgOAhcv4Sv60Iqf/6N3LgGf+yHhHgo5qI2JyYm0qZNG06dOoVer8fS0pJjx46RNWtWEhIS6Nu3Lxs2bCA+Pp4OHTqwZMkSdDr535gQQgghhBBCCPGpyL/KxUfx8OFDhg4dyqZNm7h06RKFCxcmW7ZsVKlSBV9fX7WucFRUFM+fP6dYsWJkzZoVRVHYvHkzmzdvTnPu1wOzs2bNokuXLtSqVYusWbPy888/06lTJwDy5MnDzp076dmzJ9OmTaNly5acPXtWHZuQkEC3bt3ImzcvkBS03rhxo3o/NjaWW7ducf/+fTWb0tvbmxo1alCwYEE6duzIsGHD1P6v14sOCwszupfa2lPz5uFlp0+fVt/Dv8WDy6CXHwviHSUkwsE/IZsD1CgDl2/C/mDIm3a9b0Ij4MgZcC0M9rZoTl8h9PlLyFeQtWvX8uzZMx48eIBWq6VOnTosXrwYNzc3pk+fjo+PD6dPnyY2Npa6detSvnx5unfv/vH2K4QQQgghhBBCCCMSRRJ/u6ioKL766iuaNWtG69atad26NZ06deKXX37h0KFD1KlTh5CQEGJiYgCwtrbm5cuXQFJAt02bNumWxYiNjVXb7Ozs2LFjR5prqVu3rlEt5OQDAGNjY9Xnp8VgMNCgQQNKlSqllruoWLEip06doly5ckZ9o6Oj2bp1q1FZjNdrHCdLfmbx4sVT3AsODqZs2bLqtaIoDBo0iC5duqTa/0M4NnEOmaxTHiAoRGqOHvyDiUcvsHf3XiwsLLh94wbTx09g9czFaY6ZNWkK/lX0LPRMKn/z2y+bOfz7XmpVqky2bNlYsGABer0eSCpl8+rVKyApy3/jxo3ky5cPgAYNGuDj4/M371AIIYQQQgghhBDp+SwO9IuLi+P58+fkzJkz1XICn4rBYODkyZNcvXqVgQMHfurlpElRFKP37datW9y5c4dGjRp9wlUZu3PnDi4uLhn+CHtoaCgJCQnY29v/pecnJiYSERGRbgHyvzJ3eHg4tra2atvLly8xNTU1akuNoihERkaqmdtvYzAYiIuLe+f+7+pdi7QL8boJEyZw5swZtZa5oig4ODgQFBSU5phatWrRoEEDhg8fDiRl/0+cOJF9+/YZ9fP396datWp4enry9ddfp5inYsWKtGnThkGDBn3AHQkhhBBCCCGEEAL+YQf63bp1ixIlShAZGYmlpWWqfXLkyEFkZKSa0ZaWyMhIevbsydy5cwE4efIk9+/f5/vvv0+1/4ABA4iMjGTlypVq2+HDh+nXrx/379/H0dGRhg0bEhgYSLNmzbh06ZJRgDQsLIzffvstzUDu1atXKVmyJFFRUVhYWKTaZ/ny5fTp0+edApFBQUGEhISoff38/GjYsCHe3t5q27Jly7h///5fCi57eHiwaNEizp8/r7Zt376d7NmzExoayosXLzh48CCTJk3C398fe3t7/Pz8iIiI4NGjR9jZ2dG7d291bMGCBdN9XvKhdbNmzTJq79WrFw0bNqRDhw5G7cOGDUOv1zN16tR32k9ERAS2trYEBgbSokULxo0bl2rAKj2KomBiYsLVq1eNMoefPXtG8eLFjQJqjo6OZMqUiYsXL/LFF1+kOadGo0kzUHz06FFat25NYGCg2mZmZsbWrVvZtm0bO3fu5OnTp+TLl49ixYoZjb1w4QIJCQnvVLP6dZf87knmskhTFmtbnB2zqtdhYWG4uPyvZrJGo0Gr1RIcHEzmzJlTnePNMTY2Njx58sSoz7hx45g+fTpdu3ZN9e/p0aNH8fX1Zffu3X91S0IIIYQQQgghhPgLPovgcnJd2rSCr5AUgNi4caNaZsBgMKDX69XgWWxsLKampvTt29coWJeQkMCPP/5Irly5+Oqrr1LMa21tTXx8vFFbpUqV2L17t5qRl1w6wcLCgj179qhrAMiVKxfm5uZprjs5GG5qapru3qpUqYKXl5faFh0dbfR+xMbGEhYWpgYtk23ZsoXSpUurgeXY2Fi2bNlCTEyMWjsYoG/fvgwdOhSA/Pnz8/z5c3Q6HdHR0fTt2zfF4XampqYp1jxmzBh69uyJh4cHo0aNQq/Xs3jxYqytrbl//z7x8fHUqlWLYsWK4eDgAMCjR49wdnZW1xceHs7OnTtp3LjxW593+fJl9u/frx5+t3btWtzc3LCxseH58+coisLevXuJjo6mWLFi/PrrryQmJqYaUE3+hYCdnR1Llixh/Pjx1KxZExMTEzQaDZMmTWLSpElYWlqSkJCAqamp+nH8ZBqNBp1Ol2Kder0+1e+vqakpjo6OKdoBvv76a7y9vTE1NcVgMPDNN9+wffv2t74nkPTnUK/Xc/36dbJnz57q/K//3ciIGuMGS81lkSZzU1NuzfdQA8w6nU79+a32MTcnKioqzeDym2OS+79u+PDhFC5cmD59+tCwYUOjnxeRkZF0796d8ePHp/n3SwghhBBCCCGEEB/HZxFFSi7pkF5JDJ1Ox9OnT1m5ciXdunXj119/Ze7cuZw5cwaNRoOHhwcnTpzAzs5OPWwNoEaNGgwfPpzdu3cTFhZGly5djO5HRUWRmJjI2rVradWqFR4eHlhaWpI/f37OnTtntIbExESCgoJ49uyZUdvr665Zsyb+/v7qdXLgOn/+/EZzffPNNyxevFjdGyRlBhcpUoSiRYvy5ZdfMn36dJo0aQJAiRIlWLBgAYC6/tjYWFauXMn+/ftZtmwZhQsX5tq1awQEBDBnzhwGDRrElStXqFmzpnqoHSQFHnfu3Ent2rXp27cvpqamzJkzh6ioKLRaLRqNhqtXr/Ls2TMmT55M9erVqV69Oubm5pQrV45169ahKAoJCQmcOHGCP/74g5EjR1K9enXatm1rtM/k4HpgYCA6nY7ixYsTERHBhAkT0Ol0anDX19cXS0tLJk6cSOfOnXF2dmb+/PkMHToUX19f9u/fz/jx42nTpg1mZmZMnjyZ+Ph43NzcjJ43e/ZsZsyYgZWVVap/nvLly4dGoyEhIQFHR0dOnTpFkSJF0Ov1fPvtt6xfv57z58/TuHFjDh8+zJ9//olWq1UDtRqNhuXLl+Ps7Ez//v05f/48kZGRQFKWddOmTenatSs2NjaEhYVRvXp1tFotoaGh3L17V/3e6fV63N3d6datG7NmzeLChQusWrWKp0+fYmJigomJCY8fPyY6OpopU6ZQokQJmjRpwvLlywkLCyMgIID69etz/vx5nJycmD59utE+GzRokGLv7yRPKbB1eL+x4t8tJoIYv4sEhoeqwWV7e3t8fX2NuoWHh6f7yzR7e3u1pnpa/TNlykT79u25desWq1evNgou9+3bF2dnZ4YMGfIhdiWEEEIIIYQQQoi/4LMILicLCQlRv05MTCQ2NpYsWbKowVcrKytGjRpFiRIl8PLyolGjRlSoUIEtW7bg5eVF2bJl8fPzSzHvhAkT0Gg0xMXF8ezZM6OsOTc3NwIDA5k/f74aCPb09MTd3Z3Q0FBCQkIoWbIky5YtI3fu3EycONFo7qxZsxoFRp4/f868efNo1qwZAHfv3qVgwYJGAWc3Nzdu376dYp2PHz9m5cqVrF69mufPn/PkyRP69+9Pnz59ePXqVYpD3CZPnkydOnXIlSsXkyZNYvjw4UyaNIlt27YxePBgOnToQK9evZg4caJRht+bdY91Oh0FCxYkLi5ODS6HhoZy5coVihUrZjT25cuXTJ48mZMnT/LixQvc3Nx4/vx5muVKUquxbGlpqQZ0k5938uRJrK2tKVasGJaWlpw6dYo9e/Zw7949Bg4cSNGiRfHw8GDevHlGmeI7d+7kwYMHDB06lDFjxjBs2DCGDRuW6locHR3x9vYmR44cb12nTqcjW7Zs6jo1Go36kf9ChQqRK1cuAFavXq3Wg86aNStXrlxRP+KfJUsWo194vP5LjdSe5+Ligp2dHTqdDo1Gg7m5OaamphQrVkxd89SpU/nuu+9wdnZGo9Fw5swZ6tWrx7Zt24zm69atW5pZ3OkytwIru4yNEf9Z5cqVY8WKFeq1n58fBoMh3Rrp5cqVw9vbmx9++AEAHx8fcubMCcCIESOoX78+tWrVApKy91//e7N48WIOHjzIxYsX3yszXwghhBBCCCGEEB/WZxVcTu1j1Ddu3KBw4cJAUvmIhQsX0q9fP16+fMmJEyeIjo5m7NixHDlyhNmzZxvV4E3OxE0OJuv1egICArh48WKKsgyvB/9atmxJgwYNGDx4MLGxscybNw8HBwc8PT3fuod3DXik1q9fv35s2LCBfv360bJlS5o1a8a4ceNISEigdevWKYLYkyZNIk+ePBw6dIiyZcvStGlTHB0dadmyJWfOnKFkyZJUrlyZvn37pnh2s2bN1LIYI0eOpHHjxly6dAlXV1cgKSva29ub5s2bG419+vQp165dY82aNeTOnZvffvuNevXqoSgK/fr1Y+TIkUBSxvbmzZspUqQIkBRohaQsRRsbG6pXr87169cpUaIEAAcOHCBLliy0bNkSgFGjRhEdHU25cuVITExkyZIlmJqaEhMTwxdffIGrqytTpkxh4cKF5M+f32ido0ePZuPGjep1+fLl2bJlC9myZePZs2fkyJGDpUuXUrhwYbXEiYmJCVu2bGHPnj3qAYLFixfH0dGRxMREtfyEVqulTp06asmRe/fuUaFCBQCaNm1Kv3791IPKXvdmFrWJiQn9+/dn6NChGAwGvv32W7766iuuXr1K0aJF0Wq1nD9/HgsLC/UXFc+fPyc0NJTSpUtz584dVq5cSceOHdPM+K9UqRJnzpxJ9Z7BYMBgMKjXYWFhqfYTIj3Vq1cnLCwMDw8PunTpwtSpU6lduzZarZaQkBCsra2NgsOQ9PO1SpUqDBgwABcXF9zd3enYsSMAuXPnpkePHmzcuBGtVsuyZcv4+eefgaQ6y4MHD2bPnj1YWVkRERGBVqtNt5ySEEIIIYQQQggh/l6fVepXdHS0+goPDycwMDDFQXCNGjXC3t4eZ2dncuXKxejRozlw4AAlSpRIkZG6ZcsWnJycsLS0pGvXrgCsW7eOnj17Ehsbm+Y6rK2tsbGxYf/+/SiKwvbt2wkNDcXa2ppcuXKRK1cusmfPTt68ecmSJQs//fSTOja90h5vY2Jigru7O9u3b6ddu3Y4OTkxaNAgFi9enOJAu2zZsnHhwgUuXrxIYmIis2bNIk+ePLRr147Dhw/zxx9/YG1tjZ+fHzt27DDar4mJCTt37iQkJITu3buj0WgICQmhevXqHD9+PN01litXjp49exIREUGBAgXIly8fzZo1IyEhgcWLF+Pv709ERAT379+nYsWKahA9MDCQkJAQihQpgkajwcvLi+rVqxMaGprqc2bPnk1QUBDFixdn0qRJmJqaEhUVRalSpejevTt//PEHu3fvRlEUlixZQtGiRdWxkZGRjBw5En9/fzw9PdWD9vLnz8/9+/dJTExkypQpRs82MTHh22+/JSQkhKNHj6rfx+SM6LRcuXJFzSgvXbp0irrJaUn+XoeEhDBp0iS1VEfjxo3ZsGFDqmN8fX1p0qSJ+p4WKVKE4OBgzp8/j52dHdu2baNZs2b07duX8+fPc+fOnTSfP23aNGxtbdVX7ty532ndQrxOp9OxcuVK+vbtS5YsWdi1axczZswAkn5ZePXq1RRjSpUqxYABAyhbtiw5c+ZEq9Wqh3/26dOHZs2aUb9+fRo1asSgQYNo06YNAO7u7hgMBurUqYO1tTXW1tbvX/5FCCGEEEIIIYQQH8RnFVw2NzdXX5kyZcLBwSFF1hskBaFv3LhBUFAQVlZWZM+ePdVM4M6dOxMcHMzw4cOxtLQEkuriRkZGsmnTpnTXsnz5ckxNTdHpdCxYsIArV64QHh7O48ePmTx5MjVq1MDf35/AwEAmTZqkjktMTHynvabVLzo6GoBTp04BqMH11PZXpkwZZs2aRevWrSlQoADbtm0jX758DBgwgClTpnDnzh1Gjx7N+PHjsbe3x93dPc1n29nZ0b9/f8aPH//Wtc+ePZtKlSphY2PD6tWr/4+9+4yK6voePv6FGWDogmCMBUFFjTFWLLFhV2LvBRM1EaOCGlGjJvaCLTaMmkIUa0g0scaW2GOLUURRo9EodgWVDsO05wUP9+84gBA15Zf9WWvW4p579rn3DqMv9mz24fDhw2i1WrN2FTl/zp7XczZv3pzXX3+dRYsW5XrexcWF77//njt37ijJpXXr1jF69Gj27t2Ln58fbm5uWFtb07p1a7PYpzdoNBgMQHZSKzo6mlWrVlGmTBk6duyozMnrPidOnMjatWu5evWqxbnMzEwGDx5MmTJlgOwvFnr37k3ZsmWpVKkSjx8/platWlSpUgU7OzvKli3LJ598kuf1VCoVEyZMYPr06co9P/2erVq1SjnOysri9u3b+Pn58csvv9ChQweWL1/O1KlT8fPzU3pB52b8+PEkJSUpr5s3b+Y5V4j8dOjQgatXr7Jq1SouXryofNFjMpmUv4R42syZM4mOjmbjxo0cPXpUqT62srJi7ty5JCQkcPv2bUaOHKnEbNq0CZPJZPZ6chNUIYQQQgghhBBC/PX+UW0xCmLnzp0kJyfTokULJk+eTNWqVbG3t+fMmTPs3bv3mfGurq5ERUUp7Rhyc+nSJWbMmMG4ceOIjo5m9OjRHDx4EH9/f4uNp/R6vdI3GLI3oho2bBgffPCBch5Q2ihAdlKwTZs2Ftc1mUx89NFHzJo1i5kzZ9KjRw/Gjx9Pu3btGDt2LJs2bTKbv3r1aubMmUNgYCBNmjQhKCiIYcOGsXDhQqUSMMfcuXNp1aoVgEXi0mQyAfDuu+/y+++/Kwnu3Ozfv5/du3czZcoUjh49yoQJE5g/fz4ARYtabgSXW5I053ohISF5VtfGxsbSt29fSpcuja+vL8OHD2fYsGE8fPiQGzdu4OjoiLOzc66xWq2Wjz/+mNmzZ5OZmalspti4cWOGDx9OWloa3377bb73mXOPFSpUoH///ty/f99iU0aNRsPkyZNJSEgwe38Ajh49ypAhQ9DpdBw9ehQXF5cCXa9Xr15s377dbM282NraKu0sbG1tC1U1b2dnZ9Z7XIjnUbx4cdq2bVuomMqVK5v9xYEQQgghhBBCCCH+ff5VyeWMjAw++OADwsPD8fX15dSpU0qLhH379jF9+nSLTe9y06ZNG/R6PampqVy9elXpp5vjww8/5J133qFkyZJER0fz7rvvYmNjQ8OGDYmOjsba2pqsrCzc3d1JT0/n/PnzSuLxl19+MVsrtw398rJixQoAxo0bR/Xq1Zk+fTqVKlUiKioKb29viyo9tVpNcHAw1apVo0KFCtSsWZPk5GQWL15sdj1vb2/atWuHl5cXkJ3Y7Nq1KzY2NqSlpREaGgpA2bJl+eabb/K9R5VKxbJly3j8+DFGo5GePXvSoUMH6tSpQ8WKFS3m5yRRixcvDmRv2piTcO/Vq1ee16lcuTKRkZHUrFmT8uXLY2Njw4gRI9i6dSsODg6kpKSQmJhIlSpVyMrKwtPTU6n2joiIICIiQlnr999/57fffqNx48bcvHmT3r17K32Sn7zPjRs3smvXLvR6PY6Ojsq5L774It/3JDeffPIJo0aNIikpiaFDh7J27VqL640cOZJx48aRkZGh9FV2cnJi8+bNAAWqJl60aBHz5s3D1tZW+f0+fvyY27dvs2/fPurUqVO4G89Mg7TEwsWIv9eD+7BtEzx+BNVrQfNW8KwvGi6ehx93gdEILVpDlarZ40Yj7PoBYs9m/1ylKrzVDqxVkJECWw9Q67sKyjLTp09nwoQJL/HhhBBCCCGEEEII8U/2r0ouHzhwgDfffFNpg/DFF18QHBxM7dq1eeONNxg+fDhjxowxi8nIyODEiRNkZWWRnp6utMeIjo6mTp06uLu7s337drOYOXPmULRoUX788UdMJhM2NjYA7Nu3D1tbWyIjI9m1a9czW2sUhtFoZMOGDSxfvhwAHx8ffvvtN7Zs2YKjoyOXLl2yaKXQp08fWrVqxfHjx9m4cSNXr17NtSIazNtq6PV6vvvuO1q0aEFISAg6na7A99i4cWP8/Pw4fvw4arUanU7HgwcPSE1NzbVyOSeRfO/ePdRqNVWqVCnQ9QwGA40bN+bGjRusXbsWJycnFi9ezOLFi0lMTOTNN9/k008/pXTp0tSoUUOJe/ToEWfOnOHUqVMcP36c48eP4+Liwrx581ixYgV2dnbcuHEDgBMnTlCiRAlKly6NXq+nW7durF27ll9//ZW33nqrQO8JoPyJfo6vvvqK+/fvK5uUbd++ndGjRzNv3jyluliv17Nw4UIGDhzIJ598YvGlREGNHTuWXr160bFjR0aPHk3x4sUZPXo0n332WeETywBxMWDzr/pv4b/NYIQ9R+GVouBfE2J+g12PwbtE3jFJqbDvBFSvBO6u8OMPkH4bnB3ht2twNx78a4DRBD+fBut08CkJKWlga8PZCxco7eEJIJvpCSGEEEIIIYQQ/3F/eRYpIyODe/fuodFolERbTguAe/fumc01mUxkZWXx6quvYjAYCAgIoEmTJsr52bNnKz/rdDp+//13Lly4QNOmTQF48OAB7du3p2jRonh6elKpUiX69etH48aNKV26NMeOHaN48eJkZWXx66+/8uDBAwICAqhUqRKQnUzNqbzV6XQWLTGevMe8WgzkxBuNxlz7JufMsba2ZteuXcpYxYoVOXnypHL88OFDTp06ZbZGSEgIn3/+OW+99Ra9evWidevWZGVlcevWLUqVKqXMu3fvnlny093dXbnfKVOm5HpPycnJFm0WihYtSrdu3cyefdy4cbz22mv0799fGdfpdBgMBqVf9iuvvKKstXPnTtzd3XO9nqenp3K8du1agoKC8PPzo169erRu3Zr4+Hj27t3LtGnTaNGiBRUqVKBp06Y0aNCAWbNm4evry65duxg3bhwdOnSgX79+REREkJGRQVBQEJmZmVy+fJnGjRszf/58Dh06RKlSpVi6dCn29vYUKVIEgDfeeIMTJ05Y3KNWqyUrK8vifdHpdOj1egwGA/Pnz+eLL77g4MGDyu/qm2++wd/fn65du/LZZ59RrFgxXF1dlS86Bg4cqCSin/U7gOy2Kk+21bCysqJnz570798fo9HIuHHjKFasGFqtttCtLw5OW4CTs1OhYsTfZ/+eH5m2/xQ7tu3A3t6eyxcvMnvyVFbMXZZnzCfTZ3K9gQ2fRn4FwPqVq0h89Iiho0Yyf0YYPd/pS6n/XwU/afSH2Ds4MH7aFHZs2cpJx1d4o7xvnmsLIYQQQgghhBDiP8b0F/v5559NKpXK5ODgYHJ0dMz35eDgYFKpVKbY2FjTq6++atq/f3+e66anp5vKlCljevPNN01nzpwxmUwm0zfffGNq0aKFSafTmUwmk+nIkSOmbt26mby9vU3Ozs4mGxsbE6C8WrRoYbbmihUrTF26dDGZTCZTq1atTA4ODiZXV1eTi4uLydnZ2eTq6mpycHAwqdVq5RpPO3nypAkwZWRk5Hnvn3/+ucnf3z/f923u3Lkmb29v06hRo5Sx69evm+7du2c2748//jCVKVPGbKxMmTKm33//Pd/1c+j1elOTJk1Mtra2pkmTJj1z/rVr10wVKlQwpaSkmEwmk8lgMJisrKxMCQkJBbrerVu3TKVKlTLZ2tqadu/erYxnZmaakpKSlONz586ZHBwcTPXr1zdFRkaajEajyWQymZKTk03Dhw831a1b12Q0Gk0Gg8Fs/du3b5s8PT1NEyZMMGm1WpPJZDJdvHjR9Oqrr5qKFCli+uOPPwp0n59++qnJxcXFVK5cOYvfdVxcnMnFxcV06NAhU6NGjUw3b95UzuXMTUxMNHXu3Nm0YcOGfK8TExNjMhqNpt69e5vs7e1N77zzjsWc1atXmzp06GDas2eP6fXXXzd17drVFBkZaUpOTjalpKSYoqKiTAMHDjTVqlXLdOPGjQI9X1JSkgkwe8/FP9+UKVNMAQEByrHRaDS5ubnlG9OkSRPTnDlzlOOjR4+a2rRpk+vcunXrmhYsWGAymUym4cOHm8qWLWtydXU1eXp6mj7++GPl36EQQgghhBBCCCH+txQ0V2RlMj1R0vo/SKfTKW0t/gv0ej0JCQlKj+M/48qVKzg4OFCiRD5/Wv+EJ6uU/4yYmBi8vb1xdXXNd158fDz379/njTfeIC0tTan8heznVquzC/FLlChBWlqa8nvPrWrcZDKRlpbGkCFDWLhwYa7XMxqNJCUl8fDhQ37//XeOHz/OpUuXaNeuXa6VxleuXKFbt24cPnxY2WwwODgYJycn5syZYzH/woULZhuaabVaihYtypYtW6hQoQJ6vR4fHx+zmHv37vH1118zcuRIypYty/fff8+5c+coV64cr7zyCj169ODIkSNoNJp838unJScn4+rqysEzp6Vy+R/Mw9kVL89iyvGoUaPIzMxk6dKlypinpyeXL1/Gzc0t1zVq1arFuHHj6N69OwDnz5+nT58+xMTEmM3bv38/7du359q1a3h6ehIQEEDFihUZMWIEV69epVevXnz66af59k4XQgghhBBCCCHEv1NOrigpKQkXF5c85/3PN1f9LyWWIXuTv+dJLAOUL1++UPOfJ7EMUK1atQLN8/T0JDExEbDs9ZqTWAZwcXFh/fr1SgsVrVaLjY2NkmDOysrC1taWkJAQnJzME6lly5YlMzMTjUaDjY0NTk5OnD9/nrfeeouyZctSo0YNi8StVqvF1taW8uXL4+Pjw8mTJ2nWrBmJiYl8++23HDx4EMhOgFtbW2Ntbc3Zs2epX78+hw4dombNmgDs2LGD1157jebNm+f5Hri6urJ+/XrKlSuHWq1GpVIxc+ZMdu7cya+//oqtrW2hE8tP8p8UKj2X/8E0trZcWrxSSTCr1WqL1icajYb09PQ8k8tPx+TMf1JaWhpBQUFMnjxZaVezc+dO5byPjw/Dhw9n48aNklwWQgghhBBCCCH+wySLJP5VcnoQ59aLOIdarebu3btEREQwcOBAvv/+exYuXMiJEyewsrJi5cqVHD58mCJFilgkxrVaLVu2bKFGjRpKwtrb25uwsDClF7fBYFAq4g0GAyVLlsTe3l5Zq0ePHqSnp1OsWDEcHR156623lN7c27Ztw8/Pj6pVqzJx4kS6du1KdHQ0RYoU4YsvvuDcuXNK7+cc3t7enDlzBsiudu7Tpw9paWlkZmayd+9e6tatS1xcHHv37qVFixZmz/JkUr1AylQDV8uNGcU/QGYqmddOk5CSpCSX3d3diY2NNZuWkpKSa3/4HO7u7sTHx+c7PyQkBC8vL0aNGpXnOsWKFeP27dt/5kmEEEIIIYQQQgjxP0KSy+JfKaeCGbLbV2RlZeHh4aEkhB0dHRk/fjxvvPEGBw4coF27dtStW5dvv/2WAwcO4Ofnx7Vr1yzWNZlMTJ8+nb179ypV78nJydSpU0dJ0ur1egYOHMiiRYtQqVQ8ePAAo9GoXHvSpEkkJiYSHh6urKvT6QDzSvoPP/yQ3bt3s3jxYtq2bUt0dDQPHz7E0dFRmRMcHGxWlX3hwgXOnTvHwoULuXnzJsePH8fZ2ZkjR46wc+dODAYDa9as4f79+zg7O3Po0CElKV4gGkdwLFLw+eJvVbt2bb788kvl+Nq1a2i12lw3zXwy5tixY7z33nsAREdHU7JkSeX8smXL2LNnD6dPn1Y+8xkZGdSpU4dffvlF+auBY8eOUaZMmZfxWEIIIYQQQgghhPiXkOSy+FfK7U/+L168qCRSXVxc+PTTTxk2bBjx8fEcPnyYjIwMJkyYwL59+5g/fz5hYWEWa+h0OubNm0fFihWVMW9vb3bt2pVnkvbYsWN06dJFSbrdvn0bT09Ptm7darZu7969+eSTT5QxKysrvvnmG1xcXGjSpAkTJ07E0dGRnj178s4779C2bVu2bdvGihUrlJi3336bxMREzp49i42NDUWKFKFSpUr4+fkxadIkMjIysLW1pW7duixdujTPe9ZqtWi1WuU4OTk513nin61x48YkJyezcuVKBgwYQFhYGC1atEClUpGYmIizs7NFdX7Xrl1p0KABI0aMwMfHh/DwcKWH+P79+wkNDWX79u04OjqSmpqKSqXC3t6eV155haFDhxIcHMzhw4dZv349P/3009/x2EIIIYQQQgghhPiHkOSy+FfKyMhQftbr9Wi1Wot2Eu3atePTTz/F3t6eUqVK8dFHH1G2bFmqVauW52aFGRkZ2NnZERQUxI8//gjArVu3aN68uVJ1PGjQID766CMgO2n85ptvcv/+fQDi4uKoVq0aly9ftujnbDQaLTaYLFq0KHq9nkGDBvHOO+8A2RusQXYCeOzYsUrvaID33nuP+Ph4fvrpJ5o1a0b//v2ZM2cO27dvB7IrVytWrMidO3fy3ZBx1qxZTJ06Nc/z4t9BrVYTERFB7969GTNmDNbW1hw4cADI/gImOjqa6tWrm8VUq1aNESNG4Ofnh0ajwdfXl6FDhwIQHh6OVqulZcuWynx/f38OHDjAihUr6N+/Pw0bNsTb25uoqCj8/f3/qkcVQgghhBBCCCHEP5Akl8W/0tOb1j2dyM2RkZHBxYsXefToEUWKFOHVV1/NswexTqcjLS0NR0dHHj9+zJQpU+jfvz/R0dH4+PhQpEgRQkJCzBLboaGhbN68WakOvXXrFu7u7lSpUsVifaPRSOfOnVm8eLEytnLlSn799VeWL1+ujN2+fZukpCTs7OwIDg42W2P27Nm4ubkxZ84cmjVrRr169Vi/fj2tW7fm3Xff5ciRI3h5eZGamppvcnn8+PGEhoYqx8nJyZQuXTrP+eKfq0OHDly9epVTp05Rr149ihbN7pltMpnyjJk5cyaBgYHcvn0bf39/pefypk2b8ozx8vJi3759L/bmhRBCCCGEEEII8a8myWXxP2vnzp0kJyfTokULJk+eTNWqVbG3t+fMmTPs3bvXYn58fDy2trZ4eHiYJaDfffddJk6cSJcuXQDzpN2SJUtYsmQJANu2bePDDz/k5MmTeSa7n6TX65k5c6ZZe47o6GiSk5PZvn07ffr0sYgZOHAgp0+f5tatW3h5ebFx40Zu3LjB8ePHefToEcuXL8fHx4fatWvne207Ozvs7OyeeY/i36F48eK0bdu2UDGVK1emcuXKL+mOhBBCCCGEEEII8V8gyWXxPykjI4MPPviA8PBwfH19OXXqlNLqYt++fUyfPt2iuvjcuXN4eXlhZWWl9CPW6/Vcu3ZNaS1QvHhxpcrzSQcOHGDw4MGUKlUKb29vnJycSEpKwtnZGSsrK5KSktizZw916tRRYpYuXYqXlxe9evVSxubPn8+UKVOIjIzkxIkT1K1b1+w6W7ZsYe/evcyYMYP9+/cTHR1Nnz59qFOnDnq9niFDhjB16lQ6der05964zDRIS/xzseLlykyFpFTe7tSFOzdvMXDgQObOnYuVlVW+YRs3bmTUqFHodDrmz59P7969ATAYDISEhLBu3Tr0ej2BgYEsX77cbANJgD/++IMqVaqQnp7+0h5NCCGEEEIIIYQQ/06SXBb/kw4cOMCbb75J69atAfjiiy8IDg6mdu3avPHGGwwfPpwxY8aYxezYsQM/Pz8guyLZxcWFzz//nDJlynDmzBneeecd5s6dS/369ZUYg8HA3LlzWbBgAZs3b6ZBgwbKOScnJ/bt20f58uUt7u/y5ctMmjSJQ4cOKWNffvklx48f57PPPqNq1ap06tSJrVu3WlQhnz17locPHxIQEMDdu3d59913gez+u/369WPGjBl8//33f+6Ni4sBG/lv4R/JYMTqWAw1unZn66bNDB8+nMjISAYMGJBnSGxsLIGBgSxdupS6devSpUsXatasScWKFZk9ezbR0dEcP36crKwsWrVqRZ06dQgKCjJbY/DgwWatYIQQQgghhBBCCCFySBZJ/GNlZGRw7949NBqNUp2ZkJAAwL1798zmmkwmsrKyePXVVzEYDAQEBJhthDd79mzlZ51Ox++//86FCxdo2rQpkN3nODIykrVr1wJgY2PDtGnT+Oabb/jxxx8pV64cN2/epEOHDrRs2ZLFixdTrFgxevbsya+//srevXt544038n0ek8mEyWTC2tqaDz74gF69elGtWjW0Wi0TJkxgzZo1HDp0CCcnJzp27MiNGzdo1KgRc+fOZejQoUpF6ciRI3n33Xfp1KkTJUuWZOXKlZQqVYoSJUoQGRlJzZo1GTJkCOvWrbOoQn2Wg9MW4OT87JYe4q+3f8+PTD9wmi+WL8fBwYGwsDCCg4PzTS5HRETQtGlTBg4cCEBISAhr1qxhxowZJCQksH79esqWLQtAQEAA0dHRZvFr1qzh1q1bL++hhBBCCCGEEEII8a8myWXx3GbOnEmPHj3w9fV9oeueOnWKJk2aYGdnZ/an/7a2thbVwCaTCa1WS0xMDElJSfmuq1ar6dKlCyVKlKBDhw4A3L9/n3feeYd27doxc+ZMFixYwNtvv01sbCxubm4AjBgxgrfffpthw4bx+eefM3HiRObMmYOzszM//vgjtWvXxt7eXrmOlZWVUgltMpnIzMxkxYoVBAYGsnr1agAePXpErVq1KF68OCdPnjTbVG/YsGEULVqUIUOG8PjxYyZPnszJkydZu3YtO3fuZPjw4QQHB3Pr1i0+/vhjfv75Z7777jsqVKhAs2bNqFOnDtu3b893Y7+nVfcph4uLS4Hni7/Otvvrqf/mmzg4OABQtWpVLly4kG9MTEwMAQEBynGdOnWYNm0aAAsXLjSbe+nSJXr27KkcP3z4kDFjxvD999+bVeQLIYQQQgghhBBC5JDksnguFy9eZN68ebz33nvPnPvWW28xZswYpVo4Li4Ob29vUlNTcXR0tJi/du1aBgwYwMKFC802yHv33XdxcXFh0aJFuV7nzp07NGnShMTERIoUKWJxPjMzE6PRyNGjR5WxmjVr8sYbb2A0Gvnggw+4desWTk5OuLm50aFDB4YOHUqbNm1wd3dn3bp1yqZ+5cqVAyAwMJDAwMA8n33q1Kmkp6crczw8PDCZTOh0Or777juqV69utokgZLfc6NGjB40bN8bT0xOAlJQUNmzYwO7du5VKaScnJ6pWrcry5cuV9/Hnn39m8+bNhUosA5y5dlUql/8BPJxd8fIsZjaWnJyMj4+PcmxlZYVKpeLx48fKFyBPezrGxcWFO3fuWMzbv38/sbGxbNu2TRkLDQ2lZ8+eZm1ghBBCCCGEEEIIIZ4kyWVRKK+99hqPHj1SKnQfPnyItbU19erVIz09HY1Gg7W1NRkZGdSrV48tW7YA8PvvvxMTE0O9evWUtXLWeLLa90kTJ06kV69eDBw4kDt37hAbG4ujoyM6nY6MjAw2b94MQHp6Op06deKLL75QYu3s7DAYDOj1eot1DQZDrtf88MMP2blzJyqVivj4eKysrNi8eTNxcXGcO3cOR0dHUlJSKFasGCdPnizwe7Zw4UKio6OJiooyG79x4waVKlXCzs4u1ziDwUBYWBjDhg1Txpo1a8bq1avp2bMnR44cwc3NDTc3N0aPHm0Wa2dnZ1aFWlD+k0Kl5/I/gMbWlkuLV5olmNVqtcVnRaPRkJ6enmdy+emYnPlPSktLIygoiMmTJytfYuzdu5fDhw9z7ty5F/VIQgghhBBCCCGE+B8kWSRRKBcvXlR+Xrx4MVu3bmXHjh3Y2dkxceJELl++zNdff21RhRsZGUl8fDyvvvoqAJ6enhw7dgzAYm6OkiVL8uOPPyqVmRqNhhkzZnDhwgXWr1+PXq/Ps6ewwWBgyJAh1KxZ0+Lc3bt3LZKxkJ0EzmkVMGXKFNRqNRMmTKBNmzaMGzeOJk2asHnzZubNm1eAdyrbuXPnWL16NUeOHEGj0ZidK1OmzJ/aKK1FixaMGTOGwYMH88033xQ6Pl9lqoFr0Re7piiczFQyr50mISXJLLns7u5ObGys2dSUlBRsbW3zXMrd3Z34+Ph854eEhODl5cWoUaOyL5+ZyeDBg/n8889z/YsCIYQQQgghhBBCiBySXBZ/Snh4OKGhoXh7e1OrVi1l/MKFC8THx7Nw4UKqVasGwOPHj1m5ciU3b97klVdeYe3ataxYsUKJ2bBhA87OzrRp00YZy8jI4Mcff6RDhw5KQvrmzZssW7aMvXv3AtC1a1d69epF7969Le4vMDCQuLg4du3alev9BwcHW4x9/vnnjB07llKlSnHnzh1sbW2JiooiLi6OAQMGKIm2KlWqFPh9+uSTT5g+fbrSJzeHwWDAYDDkmxgEMBqNGI1GiyT6gAEDWLZsGVeuXLHoP/1cNI7gWOTFrSdemNq1a/Pll18qx9euXUOr1eLu7p5vzLFjx5S2NdHR0ZQsWVI5v2zZMvbs2cPp06eVL3lOnDjB1atX6d69u9laRYoUYfv27TRs2PBFPpYQQgghhBBCCCH+xSS5LAolNjaWsWPHcvfuXXx8fLhy5YrFnAULFlCnTh0qVqzItm3b+Pjjj3nvvfcoViy7CvPYsWNmCSpXV1d69+7NoUOHeP311wE4cuQIPXr04N1332XBggWYTCZ69erF3LlzqVSpEhkZGQwYMIA+ffpQpkwZpS/ssGHDOHLkCEWKFLFI6D5Jr9cTFRWFv7+/Uol8584dfH196dmzJ5GRkVSoUIH69esTERFB06ZNlf7KkN2jNqd3dH5+/vlns0R6jg0bNuSaFM/N2LFjmT17tsV4jx49+OGHHxgxYkSB1nmSVqtFq9Uqx8nJyYVeQ/y1GjduTHJyMitXrmTAgAGEhYXRokULVCoViYmJODs7o1KpzGK6du1KgwYNGDFiBD4+PoSHh9O3b18g+zMcGhrK9u3bcXR0JDU1FZVKRd26dfnjjz/M1vHx8eHMmTMUL178L3teIYQQQgghhBBC/PNJclkUWFJSEt26daNjx44sXbqUcuXKWWyYp9Vq+fTTT7l69SqHDx9mz549nD17ljZt2tC2bVvWrl3Lpk2b2LRpkxLTqlUrPv74Yzp16sTJkycpUqQILVq04OzZs/Tq1YvTp0+zY8cOjh8/zo0bN5g5cybu7u4ULVqUDh060K1bN3799VdKlCjBkiVLAFi5ciVJSUl5PouVlZVFUjYkJISAgADGjh2Lm5sbM2fOxMbGhq1bt9KwYUPq1q3L9evXCQsLIyUl5ZnJ5czMTDQajUXCD6Bz584kJCRga2tLUlISpUuX5saNG7i5ueHh4cHZs2cpUaIEBoMhz9YfZcqU4Zdffsn3HvIya9Yspk6d+qdixd9DrVYTERFB7969GTNmDNbW1hw4cAAANzc3oqOjqV69ullMtWrVGDFiBH5+fmg0Gnx9fRk6dCiQ/dcHWq2Wli1bKvP9/f05cOAA3t7eFtfPbUwIIYQQQgghhBD/bVYmk8n0d9+E+PfIyMjA3t6eW7du0aRJE4vK5ZSUFFQqlVI1rNPpePDgAZ6engwaNIgdO3bg6enJ+fPnSUhIwNPTk5yPYKdOnbCxsWHDhg3KeklJSZhMJhwcHNiwYQNly5blypUr+Pr6AtmtAby9valTp45ZErdixYoMGjRIqTZ+5513+OKLL9BoNKSkpDBo0CCzfsdRUVFs2LCB3bt3k5aWRqVKlZT14uLi8PDwwNHRUam+nj9/PjVq1Hjm+1WuXDmuXr2a75xbt25RunRpMjIy0Gg0aDQarly5QqlSpfKNi4iI4O7du0ycOPGZ9/G03CqXS5cuDWM+AnepTv1bpSXCxUOcmruMmmV9LU7fu3ePU6dOUa9ePYoWLVh/7AsXLnD79m38/f2f2YpFCCGEEEIIIYQQIjk5GVdXV5KSknBxcclznlQui0Kxt7dXfo6Li7OoZtRqtUyYMEHpaWxjY6P0eF2+fDklS5ZkypQpua792WefsWLFCkwmE1ZWVkrMzz//zPbt29m0aRPNmzfnwIEDtGnTBqPRyOHDh4mMjLRYy9ramsjISKVPckZGBgsWLMDa2hq9Xm+xiaCdnR21atWiUaNGxMbGEhERAcCuXbto2LAhTk5OTJkyhYSEBD799NMCv18uLi7cuHEDLy+vPOecP3+eUqVKWWz49yzHjx8nICCgUDE57OzssLOz+1Ox4u9VvHhx2rZtW6iYypUrU7ly5UJf68qVK6SkpFC1atVcK/CFEEIIIYQQQgjx3ybJZVEoGRkZSuVjmTJlcu25DNk9jbVarZLcBRg+fDj+/v4WG4XlKF68OB999JFynJWVxZIlS5REb2ZmJiVLlsTKygorKytUKlWeLSPq1auHm5ubUkF99uxZmjZtio2NDXq9nldeecVsfufOnencubNyLYDLly/z1ltvcenSJaVS2mg05vv+PK1Pnz4sXLiQhQsX5jnn+++/N2tNUBB3795l586dhUp0F0hmWnblrPj7ZKbmeSo2NpYBAwZw5coVBg4cyNy5c5UvYvKyceNGRo0ahU6nY/78+Uqvb4PBQEhICOvWrUOv1xMYGMjy5ctRq9UYjUZ69uzJkSNHsLGxwcHBgYMHDyqV+0IIIYQQQgghhBAgyWVRSG3atOHKlSuoVCrS0tKwtbWlRIkSyvmkpCRcXV3JysrC1taW69evo9frGT58OMePH+fIkSMFvtZXX31FyZIlCQgIwGAwEB0dzRtvvJHr3PT0dCWRfPz4cWJiYsz+/F+n07F//36lYjkrK4sjR47QoEEDs3WebBURFhZGmzZtAFi3bh1FixalsF1kgoOD8fPzY8+ePbRq1crifGxsLKtXr+bnn3/Oc43vvvuOFi1a4OrqqjxLYGAgU6ZMKXS18zPFxYCN/Lfwd9PY2uLh7Go2ptVqad++Pa1btyYqKorhw4cTGRnJgAED8lwnNjaWwMBAli5dSt26denSpQs1a9akYsWKzJ49m+joaI4fP05WVhatWrWiTp06BAUFsXr1au7du0dcXBwqlYqWLVuybNmyPP/qQAghhBBCCCGEEP9NkkUShXLw4EEAbt68Se/evZk8eTItW7bEZDLx4MEDmjdvTocOHZg6dSo2NjacOXOGIUOGoNPp2Ldvn1mPFp1OB2RXOT9dgXznzh0mTJjAV199BcCSJUt49dVX8fHxwWg0YjKZsLa2JjMzE51OR/ny5Tl9+jTFixenWrVq7N69Gw8PD6Wq08PDg3379uHk5ITJZCI9PT3X3rOdO3emZMmSdOvWjQMHDvDzzz8THR3N6NGjsba2Zvjw4UoCvSAcHByIioqiQ4cOLFmyhPbt2yvnzpw5Q/v27Rk6dCi1atVSxlUqFRcvXqRUqVLEx8fz9ttvs2HDBtq2bUt6ejqdOnWiQoUKBAUFFegeCuPgtAU4OTu98HVF4Xg4u+LlaV4lvHPnTpKSkliwYAEODg6EhYURHBycb3I5IiKCpk2bMnDgQCB708o1a9YwY8YMEhISWL9+PWXLlgUgICCA6OhoAF555RWWLFmCjY0NkL0x4MOHD1/GowohhBBCCCGEEOJfTJLLotB2795Nhw4d0Gg0vP322+h0OjQaDW5ubjg7O7Nx40b27t3LgQMH8PLy4q233mLMmDEWVbY5VcKZmZk4OZknNJOSkujWrRsdO3Zk0aJFhIWF8dNPPylxmZmZ1KxZk+DgYH744Qdq165N8eLF2bFjB5MmTcLV1dWsXYCVlRUdOnQw67WcnJxMUFAQQUFBpKen06BBA65duwZAz549iYmJoWTJklSqVIlOnTqxbt06pk+fzqFDh/jhhx8K/H5VrVqVvXv3Eh8fr4wtWbKEUaNG8d577zFv3jyz+e3ataN169ZK7+n27dsrFdQajYYBAwYorQ1etOo+5fJt0i7+PjExMdSrV0+p0K9atSoXLlx4ZsyTfbnr1KnDtGnTACxatVy6dImePXsCmMVcv36dDRs25NrbXAghhBBCCCGEEP9tVqbC/p2/+M9LTU3lu+++w9vbG29vb0qVKmW22ZdWq+WXX36hUaNGL+R69+/fJy0tTamwfFkOHTqEk5MTVatWzbOXs06nIyUlBXd39+e6VmZmJkeOHKF58+bPtc6LkrMD6MEzp6Vy+R8gt8rlUaNGkZmZydKlS5UxT09PLl++jJubW67r1KpVi3Hjxil9zs+fP0+fPn2IiYkxm7d//37at2/PtWvX8PT0VMYnTZrE7Nmzeffdd/nss89e1OMJIYQQQgghhBDiHy4nV5SUlJRvIaJULotCc3Jyol+/fnmet7Oze2GJZcBi872XpXHjxgCULl2a5ORkpSXA0wwGAzY2Njx48ADITsy1bNmSUqVK5bn2rVu32Lt3L/7+/kB2BXJuieVy5coRHh5O27Zt81zL2toaJycnsyrsp5lMJvR6PV9//TUdOnTIc97T/CeFSs/lfwCNrS2XFq80SzCr1Wrs7OzM52k0pKen55lcfjomZ/6T0tLSCAoKYvLkyWaJZYAPP/yQSpUqERwcTNu2bc3augghhBBCCCGEEEJIFkmIp1hbW7NlyxaaNGmS6/nffvvNbHM+W1tbSpUqxfXr1/Nc09vbu0Cb79nY2OTaC/pJGo2Gs2fP4u3t/cz1Cq1MNXAt+uLXFQWXmUrmtdMkpCSZJZfd3d2JjY01m5qSkpLv58Xd3d2sHUtu80NCQvDy8mLUqFEW8U5OTvTp04dLly6xYsUKSS4LIYQQQgghhBDCjCSXhXiKtbU1HTt2fGblco6nq0nz8mQP6Lyo1epnznuyYnnnzp00btwYR0dHZWzatGmkp6cTFhaWb3VzrjSO4FikcDHiL1G7dm2+/PJL5fjatWtotdp8W7TUrl2bY8eO8d577wEQHR1NyZIllfPLli1jz549nD592uyzMnbsWNq0aUPTpk2B7C9Qnmx9I4QQQgghhBBCCAFQyMyTEP/7ciqXExISlFe9evX45JNPSEhI4PHjx0pLjBy3bt1SelDn9rp16xaZmZkW10pNTWXdunUWrQoA1q1bl2tMDq1Wy6RJk6hVq5bSQ/fmzZvMnTuXihUr5ptY1mq1JCcnm73EP1vjxo1JTk5m5cqVAISFhdGiRQtUKhWJiYkYDAaLmK5duxIVFcW5c+dITU0lPDyc1q1bA9ntXEJDQ1m1ahWOjo6kpqaSkZEBZLeGef/99/n111+Jjo7m888/V/o2CyGEEEIIIYQQQuSQ5LIQT8ktSfc0k8mEVqtVjnPaYuS8qlSpwty5c5VjvV6v9HR+0t69exkyZIhFtbLRaGTmzJl8+umned6DnZ0dR48epUuXLjRs2JCNGzfSt29fOnXqxIABA/K9/1mzZuHq6qq8Spcu/cxnFn8vtVpNREQEISEheHh4sGXLFubMmQOAm5sb586ds4ipVq0aI0aMwM/Pj5IlS6JSqRg6dCgA4eHhaLVaWrZsibOzM87OzgQEBAAQHBxMp06daNOmDe3atWPkyJH07Nnzr3tYIYQQQgghhBBC/CtYmUwm0999E0L8k7zyyitotVrU6v/rGpOcnIydnZ3SAiMjIwOtVktCQgJXrlyhW7duZj2XBw8eTIUKFQgNDQX+LxltZ2dnlkju168fKpWKFStWAFClShUWLVpEixYt+P777wkKCuLatWtmu3I6OTkRGxtr1nN5w4YN9O3bF1tbW27cuJHnBm85tFqtWXI8OTk5O8E85iNwL174N028OGmJcPEQp+Yuo2ZZX4vT9+7d49SpU9SrV4+iRQvWH/vChQvcvn0bf3//Z/b0FkIIIYQQQgghhEhOTsbV1ZWkpCSzvNTTpHJZiCeYTCYePXrEkSNHzNpitGrViiVLlijHaWlp6PV6ihQpAmS3o/Dw8FBe69atY/z48cpx0aJFcXNz49GjR8q1UlNT+f7773nnnXdyvZcuXbpQtmxZFi1a9Mz71mq1ODg4oFKpGDlyJHq9Pt/5dnZ2uLi4mL3Ev0Px4sVp27ZtgRPLAJUrV6Zly5aSWBZCCCGEEEIIIcQLJcllIZ5w/fp1DAYD5cqVK1Rc6dKlzZLRhw4dwtvbWzl+9OgRGRkZZgnBdevWUaxYMfz9/fNcd+TIkYSHh+fakznHpk2bGDlyJLt27eLw4cPs2rWLPn36YDQaC/UMQuS4cuUK0dHRBWoRI4QQQgghhBBCiP8u9bOnCPHf8csvv1ClShU0Gg3lypUjMzMTGxsbAGJjY5kyZQo6nY6srCzi4+PzXKdGjRrodDoOHjyYa/JYp9Mxe/ZsBg0aZNFv+UndunVj9OjRHDp0iDZt2pidS05OZvLkyaxfv54tW7ZQt25dAPbt20fDhg2ZMWMGkyZNKtwbkJmW3ZZB/H0yUy2GYmNjGTBgAFeuXGHgwIHMnTs3388NwMaNGxk1ahQ6nY758+fTu3dvILuneEhICOvWrUOv1xMYGMjy5ctRq9UYjUZ69uzJkSNHsLGxwcHBgYMHD1KsWLGX8qhCCCGEEEIIIYT4d5PkshBP2L17N61atQKyW0f88MMPVKpUyWzOb7/9RsuWLZXjnAphk8nEN998g06n4+2332b69OmEhIRw9OhRnJ2defjwIXq9nldeeQUrKytmzJhB27Zt870fW1tbzp8/n2sP5ZUrV7Jv3z6OHDlC+fLllfHKlSuzceNGi/sukLgYsJH/Fv5uGltbPJxdgeyWJ+3bt6d169ZERUUxfPhwIiMj8920MTY2lsDAQJYuXUrdunXp0qULNWvWpGLFisyePZvo6GiOHz9OVlYWrVq1ok6dOgQFBbF69Wru3btHXFwcKpWKli1bsmzZMqZMmfIXPbkQQgghhBBCCCH+TSSLJMT/d/bsWdatW8fJkyeB7GRxkyZNzDb2A9Dr9WZj169fJzExET8/P7RaLQsXLgQgMDCQH374gaZNm7J+/XoOHz7MzJkz+eOPP1Cr1QQGBlrcg8FgsKhIfTqxnJPMHjFiBMOGDcPa2rK7TbNmzf7EOwAHpy3AydnpT8WKF8fD2RUvz+xq4Z07d5KUlMSCBQtwcHAgLCyM4ODgfJPLERERNG3alIEDBwIQEhLCmjVrmDFjBgkJCaxfv56yZcsCEBAQQHR0NJC9meWSJUuUav1q1arx8OHDl/moQgghhBBCCCGE+BeT5LIQ/5+7uzsjRoygatWqAGRlZXHgwIFcK5cbNmyoHO/duxcnJyfGjBlDz549sbKyIj09HQcHB9asWcPIkSOpUqUKBoOB+fPn53rt7du3s2zZMq5cuYKnpydnzpyhevXquc7NzMykYcOGSoJbr9eTlpaGq6ur2Tyj0UjTpk1ZtWrVn31LxF/syaRyjpiYGOrVq4eDgwMAVatW5cKFC/muExMTQ0BAgHJcp04dpk2bBqB8+ZHj0qVL9OzZE8As5vr162zYsIHIyMg//TxCCCGEEEIIIYT43ybJZSH+v1KlSjF37lzlODo6GicnyyreSpUqkZCQoBzPmzeP+fPnm82dO3cu33zzDRcvXiQ8PJwpU6aQkJBAhQoVcr32yZMnsba2Zu/evTx48IBevXpx+/Zt7OzsLOY+vVHf/fv3KVWqFPv37zdLSBuNxkJvyOY/KVTaYvyNNLa2XFq80izBnJycjI+Pj3JsZWWFSqXi8ePHubZLyS3GxcWFO3fuWMzbv38/sbGxbNu2zWx80qRJzJ49m3fffZfmzZs/72MJIYQQQgghhBDif5RkkYTIg4uLy5+eZ2tri5eXl3Ls7u6Ou7t7rvF6vZ6VK1eyfPlyGjduDECJEiVYs2aN0tYgR3p6OpUrV7ZYw2Qy0bx5c5ydnc3GV6xYUbgWGWWqgWvRgs8XL05mKpnXTpOQkmSWXFar1RZfMmg0GtLT0/NMLj8dkzP/SWlpaQQFBTF58mQ8PT3Nzn344YdUqlSJ4OBg2rZtS/v27Z/36YQQQgghhBBCCPE/SJLLQrwEVlZWuVY952bRokWULFnSbHO/GTNmMHz4cPr27YtGo1HG1Wo1cXFxXLt2DW9v73zX9fb2Rq/XF+7GNY7gWKRwMeKlcnd3JzY21mwsJSUFW1vbfGPi4+PznR8SEoKXlxejRo2yiHdycqJPnz5cunSJFStWSHJZCCGEEEIIIYQQubLcCUwI8ad4enri6OhIkSJFmDZtGps2bUKtVqNWq7G2tqZLly4WMXFxcUyfPp0lS5aYjXfo0IEKFSowfvx4s3GTycTYsWOxt7dHq9Xmeh9Go5HMzEzGjh2rbNr2NK1WS3JystlL/DPVrl2bY8eOKcfXrl1Dq9XmWQmfW0x0dDQlS5ZUjpctW8aePXv4+uuvzTaEHDt2LPv371eObW1tUalUL+pRhBBCCCGEEEII8T9GkstCvCB37twhLS2NxMRE3n//fUJCQtDr9ej1eoYMGUKpUqXM5mu1Wrp3706/fv3w8/MjPj6eK1euKOdXrlzJ2rVrWbx4sTJmZ2fH7NmzWbFiBUWLFsXNzQ0rKytcXV3x8PBQXh07dmTIkCGUL18+13udNWsWrq6uyqt06dIv500Rz61x48YkJyezcuVKAMLCwmjRogUqlYrExMRc+2p37dqVqKgozp07R2pqKuHh4bRu3RrI7rMcGhrKqlWrcHR0JDU1lYyMDABKly7N+++/z6+//kp0dDSff/453bt3/+seVgghhBBCCCGEEP8qklwW4gXQ6/UMGzaMuLg4AG7fvm1WKfr48WMyMzOVFgRZWVkEBgai1WqVTQQjIyNp2bIlOp0OgJIlS/LNN98wfvx4Ro4cadbiYvz48dy6dYuGDRvy4Ycf8vDhQxISEjh+/Dh+fn6sW7cu3/sdP348SUlJyuvmzZsv9P0QL45arSYiIoKQkBA8PDzYsmULc+bMAcDNzY1z585ZxFSrVo0RI0bg5+dHyZIlUalUDB06FIDw8HC0Wi0tW7bE2dkZZ2dnAgICAAgODqZTp060adOGdu3aMXLkSHr27PnXPawQQgghhBBCCCH+VaxMJpPp774JIf7tIiMjGTZsGFevXqVYsWJUrlyZsLAwOnXqBEBAQABvvvkmCxYsYNWqVfj6+tK7d2+2bduGl5cXOp2OChUqMGfOHHr06GG29t69e7l8+TJDhgwxu97w4cPR6/X4+PhgNBrR6XSYTCYSExMpUaIEP/74I8WLFy/Q/ScnJ+Pq6gpjPgL3gsWIFywtES4e4tTcZdQs62tx+t69e5w6dYp69epRtGjBNl28cOECt2/fxt/fP98ezUIIIYQQQgghhBBPyskVJSUl4eLikuc82dBPiOek1+uZMWMGY8aMoVixYty9e5dLly7x5ptvKnMSExPx8vJiyJAhzJkzh6NHjxIdHa30u129ejWvvvqqkli+du0aN27cwN/fn+bNm9O8eXOza7Zs2ZJNmzbh5uaGi4sLVapU4dixY9SoUQOAtWvXKq0OxP+G4sWLm236WBCVK1emcuXKL+mOhBBCCCGEEEII8V8nyWUhntOFCxcwmUyEhoYCsGTJEurXr88rr7yizHn8+DGurq4EBQUxZ84cTp06Ra1atQBITU1l8uTJbNiwQZl/8uRJRo4cycWLF3P9dqhFixY8evQIe3t7ILt/c7t27bCxscFgMJCcnMzhw4cL/zCZadkVtOKvl5lqdhgbG8uAAQO4cuUKAwcOZO7cuVhZWeW7xMaNGxk1ahQ6nY758+fTu3dvAAwGAyEhIaxbtw69Xk9gYCDLly9HrVbne04IIYQQQgghhBAiP5I9EOI5Va1alUuXLqFWq7l48SJLlixh69atZnMePXqEq6srZcuWZcuWLVSpUkU5N27cOBo3bqxUOptMJvz9/Slbtixjx45l+fLlFte8ePGi2bFGo2H37t1m6/4pcTFgI/8t/F00trZ4OLui1Wpp3749rVu3JioqiuHDhxMZGcmAAQPyjI2NjSUwMJClS5dSt25dunTpQs2aNalYsSKzZ88mOjqa48ePk5WVRatWrahTpw5BQUH5nhNCCCGEEEIIIYTIj2SRhHgB1Go1p06dolu3bvTv35+mTZsq5+7du0d8fDxeXl4AtG/fXjnXuXNnNm/eTP369albty737t3jwYMHvPLKK5QrV44VK1bw3nvv4efnB2S34NDpdGg0Gosq1uTkZO7du6f0WdZqtZhMJjQaTYGf4+C0BTg5O/3p90E8Hw9nV7w8i7F582aSkpJYsGABDg4OhIWFERwcnG9yOSIigqZNmzJw4EAAQkJCWLNmDTNmzCAhIYH169dTtmxZILsHeHR0NEC+54QQQgghhBBCCCHyY/1334AQ/3aJiYkMGzaM+vXr07FjRxYvXgzA6dOn6dixI2+++Sb169enfPnyFrEJCQlUrlyZLl26MGnSJPbs2UNSUhKDBg2ibNmyDBw4UFkPYOvWrbi7u+Pp6Ym3tzfe3t6UKVOG4sWL07FjR2Us5/XBBx/8VW+D+JM8nF2pWdaXmmV98fIsBkBMTAz16tXDwcEByK6Ov3DhQr7rxMTE0KxZM+W4Tp06nDp1CoCFCxcqyWOAS5cu4evr+8xzQgghhBBCCCGEEPmRymUhnpOLiwtFihQhKiqKzp07K+NVq1alUqVK9O3b16xa+Um1atXCycmJUaNGce/ePdq3b8/Jkyext7fHzs6OsLAwpa9yzppOTk6cPXuWYsWKYTAYCA8P57fffqN58+Zs376ddevW/eln8Z8UKm0x/mIaW1suLV6pJJYhuwrdx8dHObayskKlUvH48WPc3NxyXefpGBcXF+7cuWMxb//+/cTGxrJt27ZCnRNCCCGEEEIIIYR4mmSRhHhO1tbWTJ8+3WJcrVYzZ86cAq+jUqmIi4sDspOJiYmJ/Pjjj+zfv5/mzZvTuXNnRo8ejVqt5s0338RgMDBixAj27duHk5MTP/zwA5cuXWLevHnodDp69OiRa7V0vspUA9eihYsRf15mKpnXTpOQkmSWXFar1djZ2ZlN1Wg0pKen55lcfjomZ/6T0tLSCAoKYvLkyXh6ehb4nBBCCCGEEEIIIURuJLksxN/g0KFDvPXWW+h0OqysrFi0aBGnTp3CYDCwePFiPvvsM+Lj47G3t+fMmTPUrFmTiIgIbt68SVxcHLa2tgBcv36dadOm8dlnn3H06FGcnJwoVaoUer3erOK5wDSO4FjkxT6sKDR3d3diY2PNxlJSUpTfe14x8fHx+c4PCQnBy8uLUaNGWcTnd04IIYQQQgghhBAiN5JcFuJv0KBBAx4/fsyYMWNwcnKiffv2hIaG8vjxY3788Udq1aqFm5sbn376Kb169cLa2hpfX190Oh0VKlTAxsYGtVpNaGgoXbt2pU+fPqSnp5OVlUXv3r3/7scTz6l27dp8+eWXyvG1a9fQarW4u7vnG3Ps2DHee+89AKKjoylZsqRyftmyZezZs4fTp09jbW3ebj+/c0IIIYQQQgghhBB5kSyCEH8DlUqFjY2Ncuzu7k7p0qUpVqwY27dvp3bt2hYxjRo14uzZs1SqVIkvv/ySixcvEhQUxIoVKwBIT09HrS7Y90VarZbk5GSzl/jnaNy4McnJyaxcuRKAsLAwWrRogUqlIjExEYPBYBHTtWtXoqKiOHfuHKmpqYSHh9O6dWsgu5dyaGgoq1atwtHRkdTUVDIyMp55TgghhBBCCCGEECI/klwW4h/A19eX2bNn53rOaDRiZWWF0WgkMzNTGUtPT2fkyJGULl2aUqVKMWnSJFavXk2pUqV49dVXadeuXZ7XmzVrFq6ursqrdOnSL+W5xJ+jVquJiIggJCQEDw8PtmzZovTvdnNz49y5cxYx1apVY8SIEfj5+VGyZElUKhVDhw4FIDw8HK1WS8uWLXF2dsbZ2ZmAgIBnnhNCCCGEEEIIIYTIj7TFEOIfymg0EhUVxdGjR+nbty8XLlygZcuWJCYmEh0djZWVFd9++y3dunXD2tqa4cOHc/bsWb777jucnZ3NKqOfNn78eEJDQ5Xj5ORkSTD/w3To0IGrV69y6tQp6tWrR9Gi2RstmkymPGNmzpxJYGAgt2/fxt/fX+m5vGnTpjxj8jsnhBBCCCGEEEIIkR9JLgvxDxAXF2fWisBkMmFlZcW8efNo2LAhrVq1QqPRcPfuXdq0acO4ceNo0qSJMv/hw4dcuHCBhg0b8tNPP/Hxxx/nez07Ozvs7Oxe1uOIF6R48eK0bdu2UDGVK1emcuXKL+mOhBBCCCGEEEIIIf6PtMUQ4m9y9+5drl69yooVK3j99dd58OCBci4zMxOtVsuJEyeIiori4cOHZrEGg4ERI0Zw/PhxILsSuWPHjixatIg5c+Zw+fLlP3dTmWmQliivv+qVmWrxK4iNjaV27dq4ubkxZsyYfCuVc2zcuJEyZcpQokQJvv76a2XcYDAwZMgQXFxccHBwICgoCL1e/8xzQgghhBBCCCGEEAUhlctC/A0uXrxIq1at6NSpE0OHDsXf3x8rKyseP37MvXv3GDlyJEajEbVazY0bN6hUqRL79u2jXr16aLVahgwZgo+PD6VKlWL+/Pn88MMPnDlzBk9PT95//33at2/P/v37KVGiROFuLC4GbOS/hb+SxtYWD2dXIHujxfbt29O6dWuioqIYPnw4kZGRDBgwIM/42NhYAgMDWbp0KXXr1qVLly7UrFmTihUrMnv2bKKjozl+/DhZWVm0atWKOnXqEBQUlO85IYQQQgghhBBCiIKQLJIQf4PXXnuNGzduYGVlZTbevXt3fH19sba2Vs6p1Wq6d+9O3bp1MRgMXL16lQ4dOjB58mQGDRrE6dOn2b9/P56eniQmJjJixAjOnz9P/fr1OX/+PI6OjgW+r4PTFuDk7PRCn1Xkz8PZFS/PYgDs3LmTpKQkFixYgIODA2FhYQQHB+ebXI6IiKBp06YMHDgQgJCQENasWcOMGTNISEhg/fr1lC1bFoCAgACio6MB8j0nhBBCCCGEEEIIURDSFkOIv5FWqzU7Xrt2LZ6enkyZMoXExEQSExNJSEggMjKSrKwsVCoVR44cISsriz179tCsWTOio6OVzfi2bdvG22+/zebNm1m1alWhEsvir+Xh7ErNsr5KYhkgJiaGevXq4eDgAEDVqlW5cOFCvuvExMTQrFkz5bhOnTqcOnUKgIULFyrJY4BLly7h6+v7zHNCCCGEEEIIIYQQBSGVy0L8TW7dukWtWrWwt7e3qGBevHgxixcvVo6NRiMuLi7Exsai1WrZtGkTU6dOpVixYhgMBsLDw/ntt99o3rw5JUqUwNbWFn9//0Lfk/+kUGmL8RfR2NpyafFKs+RycnIyPj4+yrGVlRUqlYrHjx/j5uaW6zpPx7i4uHDnzh2Lefv37yc2NpZt27YV6pwQQgghhBBCCCFEXiSLJMTfpHTp0mab+BXU6NGjUavVvPnmm8rGfvv27cPJyYkffviBS5cuMW/ePHQ6HT169KB8+fIFX7xMNXAtWuh7EoWUmUrmtdMkpCSZJZfVajV2dnZmUzUaDenp6Xkml5+OyZn/pLS0NIKCgpg8eTKenp4FPieEEEIIIYQQQgiRH0kuC/EPoFKpqFChAiqVymz88ePHvPXWW3z55ZdAdn/dmzdvEhcXh62tLQDXr19n2rRpfPbZZxw9ehQnJydKlSqFXq/H3t6+cDeicQTHIi/ikcSf4O7uTmxsrNlYSkqK8rvOKyY+Pj7f+SEhIXh5eTFq1CiL+PzOCSGEEEIIIYQQQuRHkstC/APY2dnx0Ucf4ezsbDa+e/dus5YZFStWRKfTUaFCBWxsbFCr1YSGhtK1a1f69OlDeno6WVlZ9O7d+69+BPEC1K5dW/kiAeDatWtotVrc3d3zjTl27BjvvfceANHR0ZQsWVI5v2zZMvbs2cPp06extjZvs5/fOSGEEEIIIYQQQohnkeSyEP8ACxcuJC0tjbS0NLPxatWq8dprrynHjRo14uzZs7Rp04Zx48bRpEkTAAYOHAhAeno6avWz/1lrtVqzzQSTk5NfwFOI59W4cWOSk5NZuXIlAwYMICwsjBYtWqBSqUhMTMTZ2dmiur1r1640aNCAESNG4OPjQ3h4OH379gWyeymHhoayfft2HB0dSU1NRaVSYW9vn+85IYQQQgghhBBCiIKQ5LIQf6P333+fI0eOFGhup06dmDZtGllZWUD2Jn/p6el8/PHHbNiwAYDU1FT0ej1bt27FYDBQq1Yttm/fbrHWrFmzmDp16ot7EPFCqNVqIiIi6N27N2PGjMHa2poDBw4A4ObmRnR0NNWrVzeLqVatGiNGjMDPzw+NRoOvry9Dhw4FIDw8HK1WS8uWLZX5/v7+HDhwIN9zQgghhBBCCCGEEAVhZTKZTH/3TQjxX9WhQwf69OlDr1698p33ySef8McffzB06FBatmxJYmIiLi4uWFlZ8e2336JSqbC2tmb48OGcPXuWQ4cO4ezsjI2NDb6+vhbr5Va5XLp0aRjzEbgXf+HPKZ6SlggXD3Fq7jJqlrX8/dy7d49Tp05Rr149ihYt2AaLFy5c4Pbt2/j7++fbo1kIIYQQQgghhBDiWZKTk3F1dSUpKQkXF5c850nlshB/oyf73NavX5/k5GQ0Gg0AiYmJvPHGG2zatEmZW6VKFe7evWvRFgPg4cOHXLhwgYYNG/LTTz/x8ccf53ldOzs77OzsXs5DiedWvHhx2rZtW6iYypUrU7ly5Zd0R0IIIYQQQgghhBCWJLksxD+Es7MzK1asoFKlSgBs3ryZ9evX5znfYDAwYsQIevfuTb169Rg/fjwdO3Zk/PjxNGjQgO7du1OhQoXC3URmWnZVrXi5MlMhKZW3O3Xhzs1bDBw4kLlz55pt3pibjRs3MmrUKHQ6HfPnz1c2bjQYDISEhLBu3Tr0ej2BgYEsX75c6b+9dOlSpk2bhqOjIxERETRr1uylP6IQQgghhBBCCCH+90lyWYi/kdFoVH4uUaKEshFbjpzKZKPRaJZ41Gq1DBkyBB8fH0qVKsX8+fP54YcfOHPmDJ6enrz//vu0b9+e/fv3U6JEiYLfUFwM2Mh/Cy+dwYjVsRhqdO3O1k2bGT58OJGRkQwYMCDPkNjYWAIDA1m6dCl169alS5cu1KxZk4oVKzJ79myio6M5fvw4WVlZtGrVijp16hAUFMTu3bsZPXo0UVFReHp60rdvX06ePFngdhtCCCGEEEIIIYQQeZEskhB/oyf7Hq9cuTLXOUuXLmXlypXMnDkTyK5SvXr1Kh06dGDy5MkMGjSI06dPs3//fjw9PYHsDfvOnz9P/fr1OX/+PI6OjgW6n4PTFuDk7PScTyWeZf+eH5l+4DRfLF+Og4MDYWFhBAcH55tcjoiIoGnTpgwcOBCAkJAQ1qxZw4wZM0hISGD9+vWULVsWgICAAKKjowFYvnw5/fr1o2PHjgB07NiRTZs2KesIIYQQQgghhBBC/FmSXP4PMplMZGVlYWNjY9bzNzdGoxGDwYCNjc1fdHf527p1K3q9ni5durzwtbVaLba2ts9sTfC0+Ph4tm7dynvvvWdx7o033mDt2rVUq1Yt19jdu3c/c/2goCCGDh2q3JdKpeLIkSOULl0ak8lEs2bNaN26NampqUqMWq1m8+bNHDt2rMCJZYDqPuXybdIuXoxt99dT/803cXBwAKBq1apcuHAh35iYmBgCAgKU4zp16jBt2jQAFi5caDb30qVL9OzZU4nr06ePWdyhQ4ckuSyEEEIIIYQQQojnJsnlf5jbt29TqlQpypQpY3EuKysLk8nE3bt3lTGdTodKpSpQkhiyN4WLi4vDx8cHyE5U5jCZTBiNRrMxo9FIhw4d2Lx5szK/VKlSZGRkYGtry7Vr17C1tTW739TUVNq0acPatWvN7sHb25vixYsrG9Y9KTExERcXFw4dOpTvc4SFhdGvX7985+Q4fPgwnTt3pl69euj1ekaOHMmkSZOwsbEhKyuLc+fOERcXR7FixYDsBN/du3cxGAyo1WqsrKwwGo1otVqzCuO1a9cye/ZsYmNjgeyN9EaNGoWzszM9evQwu4ec9ycv5cuXJz09XZnz4MEDHBwccHLKrh5OT0+nTJkynDx50iyudOnSAFhZWTFs2DDGjh3Lrl27lN8TgK2tLf7+/gV6r3KcuXZVKpdfMA9nV7w8i5mNJScnK/8GIfv3qFKpePz4MW5ubrmu83SMi4sLd+7csZi3f/9+YmNj2bZtW6HihBBCCCGEEEIIIQpLksv/MDkVwleuXFE248rx66+/0rVrV7OxIUOGsH79emxsbJTK1vT0dPR6vVKBajKZ0Gq1rF+/ni5dulCmTBkyMjKws7Mzq9Lt1q0b5cuXZ/bs2WbX0Ol0ys+2trZcunSJpUuX8vvvvyvXvX79ujInMjIy1ySxnZ0dBoMBvV5vcc5gMGBvb282NmPGDBYsWICzszNWVlZotVoSEhK4e/cuM2bMwGg0Ymdnh16vJykpiStXrvDKK68A2S0mXnvtNWrUqEFUVBSZmZm4uLjQp08fBg8ezJo1azh9+rSSWIbsak+AwYMHk5iYSFRUFAaDAZVKRXJyMu7u7jx8+BA7OzuKFCmixFWqVInPP/+cQYMG0aZNG7PKX5VKlW8lsJ2dHVFRUfj5+QHQrl07OnXqpFSVbty4kUWLFuUZn+P9999n4cKFmEymQldeP8l/Uqj0XH7BNLa2XFq80izBrFarsbOzM5+n0ZCenp5ncvnpmJz5T0pLSyMoKIjJkycrLVIKEieEEEIIIYQQQgjxZ0gW6R8mJzFYvHhxi3N6vd4sqQnZfVgjIiKU4z179tC5c2eWL1+ea5uGnGs8XT28Z88edu3axa1btyzmP9kSI6eqed++fQwdOhTITjhXqVJFmZOYmEibNm0s1jEYDHz00Ue8+uqrFudOnz7Nd999ZzY2YcIEJkyYAMDVq1dp1aoVx48fp1atWpw9e5ZOnTqxd+9es6pMgHXr1hEaGkrFihUB8PLyomHDhmzYsIHr16/ToEEDMjIyOHDggMV9XLhwgQ0bNrBz504OHDjAsGHDOHHiBDY2NhgMBiXR/XTiv2fPnrz++uv8/vvvREREKC1HMjMzmTZtGhqNBoPBgJeXFx9++KES96yKc8DiWgAjR45kyZIlFuPLly83O/7hhx9o3br1M6+hKFMNXGWjtxcmM5XMa6dJSEkySy67u7srle85UlJS8q1yd3d3Jz4+Pt/5ISEheHl5MWrUqELFCSGEEEIIIYQQQvwZklz+h8mp6r13716ulcudOnXKMy4sLIywsDC0Wi3Nmzfn888/x8rKin79+llUST7p4cOHDBw4kCJFilCkSBGOHDlC/fr186yAzcjI4JdffjFLBj+ZKIuMjOTnn3+2iAsODiYmJoaYmJhc1w0MDMx1/Pz587Rt25bk5GSzlhiPHz+mTp06LFiwgN69e6NWq8nIyGDRokVERkby2WefUbZsWTw8PGjUqBH79u0jICCA7du3Y2try7x585g0aZLSguL06dN0796d5cuXU6dOHVJTUzEajYwcOZLFixcDlslgk8mEyWTC2tqaKlWqcOnSJXx9fbGxsSEpKQmj0agk3o1Go1mlNGQn63v16qUk+2/cuEF0dLRSrZycnKxs0vYka2trJkyYwJQpU3J9zwCKFClS+F7ZGkdwLFK4GFFotWvX5ssvv1SOr127hlarxd3dPd+YY8eOKV8aRUdHU7JkSeX8smXL2LNnD6dPnzb7nObENW/ePNc4IYQQQgghhBBCiD9Lksv/MDktKEqVKmVxTq/Xm/VDhuzk5qZNm5g4cSJ6vZ5vvvlGSUBrNBqmTJnC5MmTCQ0NZejQoRabu2m1Wrp3706lSpW4cOECOp2OoKAg3nzzTb788stcK2v37t1LqVKlcu2dnCOnxzNA165diYuLo0iRIvnGHD16lKVLl/L222/zwQcfkJycTHh4OJ9//jnW1tZs3bqVhg0bmsVER0fTo0cPQkNDCQsLIygoiNWrV/P1119z7do1OnXqhI+PD1u3bmXz5s04OTmxZ88eXnnlFcaOHcuNGzeoXLkyAAMGDCAuLo5hw4bxzjvv4OLigpeXF1999VWefZ7Pnj2Ln58fKpWKzp078/XXXysV07t376ZixYoMGzYsz2c2mUzPbIvx6aefWsQ9/TnIS16V0U/3kU5OTi7QeuLFaNy4McnJyaxcuZIBAwYQFhZGixYtUKlUJCYm4uzsbPE77tq1Kw0aNGDEiBH4+PgQHh5O3759gew+y6GhoWzfvh1HR0dSU1NRqVTY29vTrVs3Bg8ezIABA1Cr1Xz11VfKlyVCCCGEEEIIIYQQz0OSy/8ger2e0qVLk5GRkeecnGpivV7P4cOHCQoKIiMjg3HjxjF48GCSkpKUuf369SMwMJCvvvqKyZMn88UXX3DhwgWlmjU9PZ1u3brh4ODA1KlT6dixIzY2Nvz44480atSIvn37smbNGoskl7+/P5MmTWLdunVKtbG3tzf379/Hw8NDSbTmyKlwXrx4MSaTKc9nc3Fx4d1331WOZ8yYwaFDhzh48CCDBg0iICDA7F70ej21atXi/PnzfPfdd0plpoeHB2XLluXbb7/l448/plq1agwbNgxra2t27dpFz5496d+/P6NGjcLb21tZ79tvv8Xe3h4rKyu8vLy4fPkyRYoU4eLFixatN3JUq1YNnU7HJ598wrlz58zObd++nUaNGvHxxx8zePBgZRO+JxkMhjzfj5dp1qxZTJ069W+5tshudRIREUHv3r0ZM2YM1tbWSpsWNzc3oqOjqV69ullMtWrVGDFiBH5+fmg0Gnx9fZXWNOHh4Wi1Wlq2bKnM9/f358CBA7Rv354NGzbg6+sLQPPmzenSpctf8pxCCCGEEEIIIYT432Zlyi/bJ/4yDx8+pFy5cjg4OJj1Q82pKH1yUzitVotOp+PGjRt8//33dO/eXWl7kZCQgKenJ9euXTNLnKakpHD27FkaNGgAwPXr1+natSslSpRgw4YN/Pbbb7Rr107puXz16lUaNmxIy5YtiYyMVCpgnZycSEhI4PDhw0yYMIETJ06g0WjIzMykT58+jBkzhurVq7N+/XqLNhd2dnZERETg7OxMZmYmgwYNYvXq1cr1IiIiuHjxojJfp9NhbW2NSqWiRYsWTJkyxaxyOTMzk4yMDIsN0H7++WdWrFjB119/TZEiRShTpgz3798nMzOTMmXKcOfOHWxsbIiPj8fKyopt27bRuHFjLl26RGpqKikpKTRt2pRDhw7h5OSEo6MjXl5e2NvbYzKZlGriJ3s2f/LJJ8TGxhIZGQnA3bt3KV++PD///LOSeD5y5AjOzs5m91q+fHnS09OV3/mDBw9wcHBQWnWkp6dTuXJli/7QgwYNIiIiIt+ezQaDgZ9++klJuj8pt8rl0qVLw5iPwN2y37f4k9IS4eIhTs1dRs2yvhan7927x6lTp6hXrx5Fixas1/WFCxe4ffs2/v7+heqdfPLkSdLS0vD393+uTR+FEEIIIYQQQgjxvy85ORlXV1eSkpLM8pJPk8rlf4iiRYuSmJgIZFchVq1alSZNmjBu3DilvUVu+vbty8cff8ysWbOURKNKpaJ8+fLKHIPBwM2bN5XE8tGjRwkICGDAgAHMnz8/1xYL5cqV44cffsDf35933nmHFi1amJ2vWLEif/zxh9lYrVq1WLduHWFhYeh0OgICAsx6yFpbW7N48WLUajVGo5GMjAxmz54NQFpamkWi9Ol+wU8m0SG7ctnHx4fDhw+bPev06dNp3LgxX375JcuWLWP48OFm62zdupUKFSowfvx4jh07RqNGjQBYtWoVMTExSnX17NmzMZlM1K5dm3HjxgHkW3mdQ6fT0bNnT7p3706NGjX46quvqF+/Pr169WLbtm1mz5mQkEB0dLRSGV3QthgPHjxg5syZjB8/Ps/7GD9+fK4bQ0J2oj+/Ptzir1G8eHHatm1bqJjKlSsrrVwKo3bt2oWOEUIIIYQQQgghhMiPJJf/YXQ6HTNmzFAqegEWLVrEypUrMRgMZGVl0b59e7766ivlvJ2dHT169CAqKspivcTERNzc3MwSifXq1WPLli00adIk33upWbMmly5dokSJEmbjp0+fZu7cuXTs2NFsvFu3bvj6+rJx40Y6dOhgsV7Tpk2pWrUqarUanU5HbGyskrROT0/n8ePHFu+FyWRSkswbNmyw6LkM2QnfzMxMbGxsUKvV7N69G4DNmzejUqks+jyr1WoMBgN2dnZm70FYWBjwf9Xf69ato0iRIsD/VZBnZmbm+54lJSXRrVs3Hj58yPbt24Hs3tffffcdNWrUYMKECcp1bt68iclkokyZMvmumdvznjx5kkGDBuU7b9asWYVaF4DMtOxqW/FiZKaaHcbGxjJgwACuXLnCwIEDmTt37jOriDdu3MioUaPQ6XTMnz+f3r17A9lfpISEhLBu3Tr0ej2BgYEsX75c2Qh06dKlTJs2DUdHRyIiImjWrNnLeUYhhBBCCCGEEEL8Z0ly+R9m7dq1PHz4kClTplC1alUAPvjggzwrlyHvTdue9GQCy9ra+pmJ5RxPJ5YNBgPOzs5UrlzZ4p4yMjIICQlh+fLlBAQEmFUef//999y/f19p72A0GtHpdPz0009AdsI0KyuL69evK+08IiIimDp1KjY2NlhZWdGoUSNeffVVpRVATjsJa2tr0tPTWbVqlUUV6KVLl1i0aBEAly9fpkKFCmRlZaHVajGZTBaJvZx2IwBRUVHcvn2bS5cuMX369DyrllNTU9m2bRuxsbH06tULT09Pvv76a7M/GfDx8eGLL77A1dVVGdu8eTPNmzc3+/2ZTCaz6xgMBot73Lt3L8nJyfj7++d6P88lLgZs5L+FF0lja4uHsytarZb27dvTunVroqKiGD58OJGRkQwYMCDP2NjYWAIDA1m6dCl169alS5cu1KxZk4oVKzJ79myio6M5fvw4WVlZtGrVijp16hAUFMTu3bsZPXo0UVFReHp60rdvX06ePFng1htCCCGEEEIIIYQQBSFZpH+QGzduKAmhM2fOUKlSJV555RUaNGhAbGysWR/e+/fv8/rrr1OsWDFMJhPffPMN33zzTZ5rP6udg1arLdDmcnq9Hl9fX6X6Njk5GZ1OR9OmTSlRogQrV66kS5cu1K1bl6lTp9K+fXsAWrZsSZMmTZQ2Gdu2baNbt24cPXoUa2trjEYjaWlpODg4KNcaMmQIQ4YM4erVq3Tt2pXWrVvz+eefY21tzU8//URYWBgZGRmsX78+1w33UlJSqFatGu3bt+f1118nMjJS2dDQYDCQkpKiJIDT0tLw8vLi8ePH2NnZUa1aNQ4ePEjJkiVp3bo1Xl5eZGVlcezYMXbu3ImjoyMAjx8/JiAggNKlS7Nw4UIGDhxIs2bNOHDgAL6+vri7uyvXq1GjBrdv3+b27dt4enoSHh7O9OnTMRqNSoJZr9eTlZUFwJIlS1i2bJlZElmr1fLhhx8yZMgQ5R5epIPTFuDk7PTC1/0v83B2xcuzGJs3byYpKYkFCxbg4OBAWFgYwcHB+SaXIyIiaNq0qdImJSQkhDVr1jBjxgwSEhJYv349ZcuWBSAgIIDo6GgAli9fTr9+/ZS/LujYsSObNm1S1hFCCCGEEEIIIYR4ESS5/A+Rnp5Os2bN6NSpE927d6d79+7069ePr7/+mp9++omWLVuSmJiotGVwdnYmPj4egKysLHr27JlvW4ychOXTpk+fzvTp07G1tSUtLU1pA5EjLS2NJUuWMHjwYCC7klav12MwGFCpVFy+fJlixYrx7rvv0rdvX6ysrPj222+ZN28ed+/eBeDLL7+0qNq9fPkyAK1atVLGTCYTSUlJTJw4UUmKGQwG6tWrR0JCAvHx8Xh6emJjY4O9vT0PHjygRo0aVKtWja1bt1pUY3/55ZccPnyYY8eO4erqqiR5U1NTOXHiBHFxcfz888/Y2dkprQMqVqxIxYoVlT7Ufn5+lC1bVtnMr3///tjb2zNjxgzl/pKSkjhx4gTff/89kF19vmbNmjx/13v37kWtVtOpUyfGjh1L7969leuZTCZ++uknRowYgclkwmg08ttvv9GtWzdatGjBypUriY2N5fLly6xYsSLPa0B2JXmrVq3YtGlTvvOeVN2nXL5N2sWfFxMTQ7169ZQvUKpWrcqFCxeeGRMQEKAc16lTh2nTpgGwcOFCs7mXLl2iZ8+eSlyfPn3M4g4dOiTJZSGEEEIIIYQQQrxQklz+h3BwcGDnzp1mFbgVKlRg8uTJTJ48Od/Y0aNH51l1XKRIkXyrlm1tbenTpw+RkZG5nm/Xrp3ShgKy21lMnz6duXPnmiVEhw0bxrBhw5T2Fnv37qV+/foABAUFMXfuXC5fvqy0ynj06BHOzs6cOXPG7HparZZJkyYpyWWVSoW7uzt9+vTh/PnznD9/XtkQ0NPTk5s3b6LRaOjTpw8lS5bk5MmTyloNGjSgYsWKfPnllxbP1ahRI9566y2zXtSdO3e2mGdnZ4e9vT2Q3Vrk999/V3raAnh4eBATE4O1tbXZeExMDE2aNOHy5csUKVJEaW9hbW2NSqXC2tqaefPmERYWhlqttmh9YTKZCA8PZ+LEibzzzjv4+fkBMHjwYL799lveeecd+vfvD2QnuI1Go/Le6vV6VCoV8+fPJyYmxuKZ8nPm2lWpXH5BciqWcyQnJ5v9+7ayskKlUvH48WPc3NxyXePpGBcXF+7cuWMxb//+/cTGxrJt27ZCxQkhhBBCCCGEEEI8D0ku/4P4+vr+qbgnK4ILKydBnJ+nezpPnDiRiRMnFuo6v//+u/Lz2rVrGTp0KHfu3Hlma4ejR49y+fJlvvrqKxYsWJDv/T6dYHdxcSEjIyPXuSqVSulpnR8rKyuzxO+TCeQcTybfITsBHxISQnBwMJ6engBm/aeflNv4hQsXGDRoEI8fP2bv3r3Url3b7LyDgwPJycksWbKEYcOG8csvv9CzZ08uXbqEvb09e/fuZcaMGXTs2LFAv98n+U8KlZ7LL4jG1pZLi1cqCWa1Wm32ZQZkb/aYnp6eZ3L56Zic+U9KS0sjKCiIyZMnK5+3gsQJIYQQQgghhBBCPC/JIv3HGY1GVq9ezdq1a/M8361btxd2veTkZMaOHUuvXr0K1DN44sSJSoJUpVLx2muvYTKZlI38TCYTOp2OlJQUzp8/b9bSITMzkxUrVrB582aLde/du5dnq5Cnpaenk5iYqBzrdDo0Gg3Ozs65zv/kk0/4+eef6devHw8fPiQ+Pp5KlSoV6FrLly/ngw8+YOjQocyePdsiGZnDwcGBL774gmLFivHHH3/Qrl07OnfuzKRJkzhw4ADVq1cv0PUslKkGrrLp23PLTCXz2mkSUpKU5LK7uzuxsbFm01JSUiy+nHiSu7u70v4mr/khISF4eXkxatSoQsUJIYQQQgghhBBCPC9JLv/HmUwm3nnnnXzbYhiNRiC7MtjJyQmNRvPMiliTyUSJEiU4d+6c2Vj//v158OABe/bswdvb2ywmMTGRTp06Kffy9ddfc+PGDerVq6fMuXjxYoGfberUqUydOrXA8/MSHBxMcHCw2djYsWOZPXu2xdydO3cyf/58atasCcCuXbv44IMP2LVrF7Vq1Xrmte7cuUOzZs0s+uk+Ta1W88UXX9C5c2c8PT1ZtGgR586dY/z48aSkpLB8+XIOHz5ciKf8/zSO4Fik8HHimWrXrm3WouXatWtotVplk8u8Yo4dO8Z7770HQHR0NCVLllTOL1u2jD179nD69GmzvzDIiWvevHmucUIIIYQQQgghhBAvgvWzp4j/ZXq9nrVr16JWq3N97dq1C71eD2RXDsfHx5OQkGD26t+/Px988IHZ2IMHDyySm6NGjWLTpk2UKVOG69evW7w++OADs0rdmzdvMnfuXLNWFOXKlcPLy4ty5cpRvnx5ypUrR5kyZfDw8CApKQmA1q1b4+npibe3NyVLllR+zu3l4eGhbM6Xly+++IKMjAwyMjJIT0/n0aNHubYF2bFjB4GBgXzzzTeULl0agMDAQEaOHEnz5s05fvz4M38fdnZ2BW5lUb16dVq3bs2DBw+oX78+QUFBxMfHk5KSQt26dfON1Wq1JCcnm73Ey9W4cWOSk5NZuXIlAGFhYbRo0QKVSkViYmKufdO7du1KVFQU586dIzU1lfDwcFq3bg1k91kODQ1l1apVODo6kpqaqrSB6datG8uWLeP27dvcv3+fr776SokTQgghhBBCCCGEeFEkufwfN27cOPR6PQcPHqRcuXLo9XquXbtGkSJFSEtLQ6/XM3DgQGW+k5MTKpWKpUuXsmPHDrO19Ho9n3zyCZmZmahUKooUKQJkt6d47733WLVqFTNmzCAuLi7XRO+iRYvM+ht/+OGHFpvsXb16lRs3bnD16lWuXLnC1atXiYuLIyEhQek9vXv3buLj47l+/TohISG0b98+12T29evXSUhIYMKECfm+RzY2Nmg0GjQaDfb29ri5uVm09Fi4cCF9+vTh66+/pkmTJmbnPvroI4KCgmjTpg2//vprgX4vBZWRkcH9+/e5cuUK1tbWlC1bFrVanecGjzlmzZqFq6ur8spJhouXR61WExERQUhICB4eHmzZsoU5c+YA4ObmZlbln6NatWqMGDECPz8/SpYsiUqlYujQoQCEh4ej1Wpp2bIlzs7OODs7ExAQAED79u1p3rw5vr6++Pj4UKNGDbp06fLXPawQQgghhBBCCCH+E6Qtxn/Yhg0b+Pzzz/npp59QqVTKhl82NjY8fPgQGxsbMjMzadCgAatWraJKlSoAPHjwgHHjxrFlyxaz9VQqFYcOHSI6Opp169Yp4ydOnODy5cscP36cuLg4ypQpw5UrVyzuZ8qUKdy7dy/few4MDOTSpUsW4y4uLuzbt89ifN++ffTu3fvZb8Zz6NatG7/++iv79u1T2mE8be7cudy5c4fQ0FAOHTr0Qq4bGxvLvn37GDJkCCNHjmTYsGGcP38eR0fHPNuc5Bg/fjyhoaHKcXJysiSY/wIdOnTg6tWrnDp1inr16lG0aHZ/a5PJlGfMzJkzCQwM5Pbt2/j7+yu9kzdt2pRnjJWVFWvWrGH48OGkpaXh7+9v9sWNEEIIIYQQQgghxIsgyeX/sGbNmjF48GDWr1+Pr6+v2cZ5ANbW1nzxxRckJydToUIFJe7jjz+mY8eONGvWzGy9nISWn58fc+bMYezYsQD4+/srLTLi4uKUyuWnJSYm0qtXr3zv+Y8//uCTTz4xqw5OSEigatWqFnP1ej2XLl3iww8/5MMPPzQ7l5qaytChQ1mwYEG+1yuIjz/+GG9vb9zc3PKcY2VlxYoVK0hLS3vu60F2MjI4OJgJEybQvXt39u/fz4ABAwgPD0ev1/PRRx8xaNCgPOPt7Ozy3CxQvFzFixenbdu2hYqpXLkylStXLvS1ateuXegYIYQQQgghhBBCiIKS5PJ/WNGiRZk4cSITJ040qzTOqXC8e/cukyZN4rvvvlOqJTds2MDmzZvz3FjP1dWVDRs20KBBA/z8/JQNxZ5U2MrlJ6s6n9y07Em5javVam7cuJHrfH9/f6pXr57rucKqUaNGgeYVJKH7rHYWOc6cOYOjoyNBQUFYW1tz7949mjdvTteuXTEajbRu3ZqIiIgCrWUmMw3SEgsfJ8xlpuY6HBsby4ABA7hy5QoDBw5k7ty5z6wo3rhxI6NGjUKn0zF//nylEt9gMBASEsK6devQ6/UEBgayfPlypUf50qVLmTZtGo6OjkRERFh8GSSEEEIIIYQQQgjxvCS5/B9lMpnQ6XQEBQXh4+NjtmleDmdnZz799FOaNm2KVqvF1taWnTt3smjRIjw8PDAajRiNRu7du2dWtVu9enUWLVpEZmamxZq5JU9NJhOHDx/m7NmzlCxZ0uK8VqvFaDQCYDQa6d69u1mSNudcfgwGA7GxsajVau7cucOJEyf47LPPzObcuHEDa2trs/dCp9ORlJRkkfTW6/XY29srbQ1yu+eCJooBfvzxRzZs2MDu3btp3LjxM5+lRo0aLF68WBkLDg4mODhYubdr164RHR2NRqMp8D0AEBcDNvLfwougsbXFw9lVOdZqtbRv357WrVsTFRXF8OHDiYyMZMCAAXmuERsbS2BgIEuXLqVu3bp06dKFmjVrUrFiRWbPnk10dDTHjx8nKyuLVq1aUadOHYKCgti9ezejR48mKioKT09P+vbty8mTJ/P8vAohhBBCCCGEEEL8GZJF+o+Ki4ujfPnyaDQas2RqziZ8rq6ulCpVCshOXGZmZvLHH3+wYsUKZe7NmzcpV64cRYoUISQkxGz9oKCgXK+bW8LZysqK0NBQUlNTGTVqlMX5hw8fotPpgOwE3YYNGyzaYjzZtiM3KpWKAQMGcP78eUqXLk1wcDCvvfaa2ZyWLVsSFxdnkWj/+OOP+fjjj83GsrKyGDFiBPPmzcv1ellZWbk+a16KFy/OiRMnaNGixTM3GExKSsr3vI2NDUFBQZhMJmXDuII6OG0BTs5OhYoRufNwdsXLs5hyvHPnTpKSkliwYAEODg6EhYURHBycb3I5IiKCpk2bKptqhoSEsGbNGmbMmEFCQgLr16+nbNmyAAQEBBAdHQ3A8uXL6devHx07dgSgY8eObNq0yWxzTiGEEEIIIYQQQojnZWXKbycpIZ7h8uXL+Pj4YGNj81zrGI3GPFtevChZWVlKe4+XfZ0dO3bQsWPHl7aJWkpKCvb29rlWnP8ZycnJuLq6kpSUhIuLywtZU5ibOnUqJ06cYMeOHUB2xX7RokV59OhRnjFNmzYlICBA6Rl+7Ngxpk2bxs6dOy3m1qtXj549ezJy5Eh8fHyYM2cOPXr0AODrr7/m0KFDLF++/CU8mRBCCCGEEEIIIf7XFDRXJJXL4rk8q2K4oF52Yhn4SxLLkF2JPXXqVJKSkujXr1+BYhYtWsSECRNITU1l3rx5fPXVV/z22295zp8wYQIpKSmsWLGCrKws7Ozs0Ov1ymaMf9aZa1elcvkFeLpqGbL/U/bx8VGOraysUKlUPH78OM/NIJ+OcXFx4c6dOxbz9u/fT2xsLNu2bStUnBBCCCGEEEIIIcTzkOSyEM/J1dUVFxcXVCqVUoGdmZnJmDFjmDx5sjIvIyMDOzu7XDcZ9PT0xNnZGcjude3q6moxJ8eBAwf44YcfOHLkCDqdDisrK6ytrbGysiIrK4u3336b6OhorK2tadasGcuWLSvws/hPCpWeyy+AxtaWS4tXmiWY1Wq1xYaOGo2G9PT0PJPLT8fkzH9SWloaQUFBTJ48GU9PzwLHCSGEEEIIIYQQQjwvySIJ8ZxyeiD/8ccftGnThv379ysbEw4ZMoRy5coxevRoi7icxLBarcbBwUGprNZoNGZtRq5cuUL58uUBOH36NAMHDmTr1q288sorDB06lM2bN2M0GvHy8iIoKIhFixYpsYWuCC9TDVxl07fnkplK5rXTJKQkmSWX3d3diY2NNZuakpKSb0W9u7s78fHx+c4PCQnBy8vLrF95QeKEEEIIIYQQQgghnpckl4V4QcqWLUvPnj1Zs2YN48aNQ6/Xs2HDBg4cOGAxV6/X4+vry4IFC+jSpQtWVla59mdOSkqiUqVKfP3113Tv3h0HBwciIyPR6/WMHz+eTz/9lGXLlqFWq7l169bzP4TGERyLPP86wkLt2rX58ssvleNr166h1Wpxd3fPN+bYsWO89957AERHRytfXAAsW7aMPXv2cPr0abMvEnLimjdvnmucEEIIIYQQQgghxIvw8hvdCvE/7vbt26hUKvz8/Ni5cycbN27Ez8+PevXq4e3tTf/+/XnjjTfw8PBQYtRqNfXq1WPt2rX5rn3w4EHs7OwICAgAoFKlSjRs2JDx48fj7OxMQEAAr7/+OgaDgddee40BAwZQrlw5XF1dcXV1xd7enocPH1qsq9VqSU5ONnuJl6tx48YkJyezcuVKAMLCwmjRogUqlYrExEQMBoNFTNeuXYmKiuLcuXOkpqYSHh5O69atgew+y6GhoaxatQpHR0dSU1PJyMgAoFu3bixbtozbt29z//59vvrqKyVOCCGEEEIIIYQQ4kWRymUhnpOdnR329vb8+uuvACxYsIBmzZqhVqtZs2YNEyZM4P79+zRp0sQsrm/fvnTr1k1pq5Gbn376ic6dO+Pk9H+b7K1evZodO3awceNGOnXqRNGiRVmzZg39+vXj8ePHLFu2jLVr1xITE8Mnn3xi0ecXYNasWUydOvXFvAGiQNRqNREREfTu3ZsxY8ZgbW2tVLW7ubkRHR1N9erVzWKqVavGiBEj8PPzQ6PR4Ovry9ChQwEIDw9Hq9XSsmVLZb6/vz8HDhygffv2bNiwAV9fXwCaN29Oly5d/pLnFEIIIYQQQgghxH+HVC4L8YLo9XqGDx/Orl278PHxoUKFCjg4OFCtWjVOnjxpMb9Vq1bY2dmxadOmXNfLzMxk3bp1vP3228rYkSNH+Pjjj1GpVNjb21O+fHnc3NwYM2YMHh4elC1bFnt7e6XFhkajybXdxvjx40lKSlJeN2/efEHvgshPhw4duHr1KqtWreLixYtUrlwZAJPJZJFYzjFz5kyio6PZuHEjR48exd7eHoBNmzZhMpnMXjnJaisrK9asWcPBgwfZsWMHW7duzfVzIIQQQgghhBBCCPE8pHJZiBfk5MmTPH78mOvXr9OgQQNlfMqUKVSoUMFivq2tLW+99RbffPMN77//vsX5b7/9FltbW1q0aKGM/fbbb4SHh9O7d28AatSowY0bNwBwcXGhcePG/PDDD8+8Vzs7u1wrmsXLV7x4cdq2bVuomMqVKyuJ6MKoXbt2oWOEEEIIIYQQQgghCkqSy0K8IG+++Sb16tXD1tYWnU4HZCcSGzRogMlkyjVmypQpuLi4cOLECYtzAQEBlCxZEpVKpYzlbOyW4/z580B2y4WUlJTnf4jMNEhLfP51/ssyU5UfY2NjGTBgAFeuXGHgwIHMnTv3mRXEGzduZNSoUeh0OubPn698kfDk+aVLl7J//35lLCUlhZEjR7J9+3Y0Gg2jRo1i2LBhL/a5hBBCCCGEEEIIIZ4iyWUhXrK8EssAFStWzPOcp6cnzZs3f+b6Dx8+xGQyERkZyc2bN5k4ceKfuk8A4mLARv5beF4aW1ucbTW0at6K1q1bExUVxfDhw4mMjGTAgAF5xsXGxhIYGMjSpUupW7cuXbp0oWbNmsrnZPfu3fTr18+iInnIkCHcvn2b48ePc/36dbp27YqDg4PFlxFCCCGEEEIIIYQQL5JkkYR4Tk8mj7OysqhYsSJVqlQBwMPDAwCDwWBWsZqeno7JZMLBweGZlax6vZ7k5GTc3d2VMaPRyG+//Ubt2rVxdXUlICCAy5cvU6NGDR48eMCdO3fMKp4L6uC0BTg5Oz17osiXh7Mrp48cJSkpiQULFuDg4EBYWBjBwcH5JpcjIiJo2rQpAwcOBCAkJIQ1a9YwY8YMrly5QkhICMHBwfzyyy9KjFar5dtvv+XYsWN4e3vj7e3Ne++9x5YtWyS5LIQQQgghhBBCiJdKkstCPCetVqv8bGdnR2xsrNn51atX8+mnn9K/f39l7IsvvmDkyJFYW1ubJZfVarXFzwaDAZVKhV6vV451Oh2lS5cmNjaWMmXKmF0vKCiIH3/8kS+//LLQz1LdpxwuLi6FjhOWVsbEUK9ePRwcHACoWrUqFy5cyDcmJiaGgIAA5bhOnTpMmzYNgKJFi3Ly5Ek2b95sllxOSkpCp9Ph5eWljKlUqj/15YIQQgghhBBCCCFEYUhyWfzPS01NJT09nWLFir2U9UuVKkVqamqe5zt37kzPnj3NNtAbPHgwgwcPRqPRKGM5Fai9evXCxsZGGTeZTGb9lFUqlVIt7ejoaHG9zz//HGtr6z/1LGeuXZXK5T/Bw9kVL0/zz1dycjI+Pj7KsZWVFSqVisePH+Pm5pbrOk/HuLi4cOfOHYA8Yzw8PChdujRbtmxh4MCBpKWlsWHDBkJDQ5/3sYQQQgghhBBCCCHyJcll8ZcxmUwYDAYyMzNJTk7m0aNHSguH33//nVOnTlGzZk2lUhMgMjKS8PBwTp8+/aevGxkZyerVq82qPZ92+fJlKlasSNGiRZ+5XmJiIt999x0dO3YkKyuLzz//nKFDh2I0GjEajUoSefbs2aSnpyvPk5mZiVqtRq1WmyWVc1hbWzNmzBhUKhV9+vRRxq2srMyqiX/++WdCQkI4c+YMAPb29rz++utma507d46LFy9StmzZZz7Pk/wnhUrP5T9BY2vLpcUrzRLMarXa7AsFAI1GQ3p6ep6J4qdjcubnx9ramq+++orAwEA2b97M6dOnyczMpG/fvs/xREIIIYQQQgghhBDPJlkk8ZfIysrCx8eH+Ph4nJ2dcXFxISsrC61WS0BAAMWLF6dp06aULl3aLM7e3h5nZ2fleO3atQwYMABHR0cMBgMajYb4+Ph8r21nZ4e9vX2+c3KStwkJCcpYRkaGWVxWVha2trZUqVIFJ6fs6l5bW1u+/PJLHB0dcXBwIDQ0FFtbWyC7CtVkMrF69WolftWqVbRs2RKAjh078uuvv5pVKRsMBkJDQ/noo48wmUxotVqqV6/Orl27zN4TOzs7zp8/z+uvv55rohrIczxfZaqB67MT7OIJmalkXjtNQkqSWXLZ3d3dokVKSkqK8vnIjbu7u9nn+Vnzc7Rs2ZIbN25w+fJl2rRpw+jRo6W9iRBCCCGEEEIIIV46SS6Lv4StrS03btww6wMbERHB2rVrWbNmjcV8g8GA0WhEpVJhZWWFyWRCp9Oh0WgICAhg69at/Prrr3Tu3PmZ17aysnrmpnk5/Y1Pnz7NvXv3eOutt/jggw9wcXFh3rx5ALz77rs0atQIwOw5+vTpw8aNG9mxYwe9evVSxhctWkRqaioTJkzI9ZpZWVksWbKELl26cOPGDc6ePUu7du0A+OOPP/j111/p0aOHWcw333xDamoqGRkZNG3alCtXrqBWq5k9e7bZvL59+5ptNFhgGkdwLFL4OGGhdu3aZn2vr127hlarNduYMbeYY8eOKRvxRUdHU7JkyQJdT6PRcPnyZaysrPjggw+e696FEEIIIYQQQgghCuLPNWYV4k/IyspCp9Pled5oNJKWlgbA999/T/HixRk4cCDHjx/Hy8uLwMBAJdmco6Cblun1ehITE5XXw4cPefDggcU8k8nEoEGDSElJ4cCBA1SsWBF/f38MBgP79u3Dz8/PIiYkJIRt27YB0KRJE4oXL463tzfTpk1j/vz5eHt7U7x48VxjTSYTmZmZnDt3jrlz5yrjv/32G4sXL8ZoNJKZmamML1++nOvXr+Pg4EDLli3ZunUrPXr0YOPGjWavTp065VvxqtVqSU5ONnuJF6tx48YkJyezcuVKAMLCwmjRogUqlYrExEQMBoNFTNeuXYmKiuLcuXOkpqYSHh5O69atC3Q9o9HIlClTmD59urKJoBBCCCGEEEIIIcTLJJXL4i/TunVrzpw5oyQ9tVotmZmZeHh4ANnVyhkZGSQlJdG9e3e6d+9Oly5dePToEQcOHACyk84FTSg/6ciRIxZ9bl955RXu3btnNlarVi169erFgAEDMJlMvPvuu6xcuZJRo0bh6upKrVq1zOavX78ea2trSpYsSaNGjbC1tSUqKoomTZqYVS7/9NNPTJ482SzWZDJx48YNqlWrRlZWFvHx8VSvXh3Ibodw//59qlevjo+PD1u2bEGv13PmzBkmTJjAjz/+SFhYGO+++y5JSUm5PnNAQAA7duzIdSPDWbNmMXXq1MK+jaIQ1Go1ERER9O7dmzFjxmBtba18jt3c3IiOjlZ+3zmqVavGiBEj8PPzQ6PR4Ovry9ChQwt0vdWrV6NSqejfv/+LfRAhhBBCCCGEEEKIPEhyWfxlDh06ZHac0xYjJ+H2tPT0dH766ScqV67MunXrCAwMRKfTFagH7dMaNWrEnj17lOP8qqgnTZpE+fLlGTJkCNbW1nzyySfUr1+f6dOnW8y9desWv/76K3q9nkaNGpGVlaX0hH748CFGo5GoqCjS0tKUJHqOzMxMKlWqxKVLl9ixYwdTp05l3bp1ABw+fJiVK1eavWe///47tWvXVtYpU6YMf/zxB9euXWPgwIH07duXW7duceXKFaZMmUKlSpXyfD/Gjx9PaGiocpycnGzR71o8vw4dOnD16lVOnTpFvXr1lA0j82tZMnPmTAIDA7l9+zb+/v4Wn/f+/fvnmkDOa1wIIYQQQgghhBDiZZHksnjpclo7aDQarK2f3YklMzMTtVrNmjVrsLKyQq/XM3HiRKytrUlNTcXR0bHQ92BtbW22wV1+m90ZjUaysrI4cuQIAF5eXtja2uZ67x9++CGRkZHs3LkTQEmU9+/fny1btjBs2DBeffVVBg8ebNH3OS0tTUk2lipVitq1a7No0SLlfPv27c3mv/baa/z444+cOXNGGdNqtfj5+REXF8fhw4fR6XRkZmayfft24uLi8kyg29nZYWdnl+d7IF6c4sWL07Zt20LFVK5cmcqVK7+kOxJCCCGEEEIIIYR4MSS5LF66a9euUaVKFezt7c0StE+3xciRkZHB119/TVhYGG+//TaxsbHMmjWLu3fvcvPmTYoXL/5S73fWrFn06dOHXbt28d133/H999/TqlUr5s2bx/vvv59rzJOJ46VLlxITE8OYMWN48OABO3fu5KeffmL16tVmifF79+5RokQJmjZtqmx2+GSv3O3bt1O2bFm6du2a571ev34do9GInZ3dMzctLJDMNEhLfP51/tc9uA/bNsHjR1DlDfByeWbIxo0bGTVqFDqdjvnz59O7d2+L80uXLmX//v0Wsenp6VSpUoV58+bl+3kQQgghhBBCCCGE+CtJclm8dOXKlSMjI8NiPL+2GDNmzODVV1+lSZMmxMbG0rJlSwB69uxJhw4dXtq9XrhwgZUrVxIbG0tgYCAnT57kwIED/Pbbb/To0YMlS5bkGZuRkcG0adNYv349Bw8e5LvvvsPd3Z2DBw/Su3dv6tevz759+yhatCjp6ek8ePCA4sWLs3//fm7cuEGzZs3Yvn07pUqVYsGCBezZs+eZicRvv/2WMWPGkJWVha+vL5CdiLxw4QLff/994d+ruBiwkf8W8mUwwp6j8EpR8K8JMZdQq0rg4eyaZ0jO52np0qXUrVuXLl26ULNmTSpWrAjA7t276devH7Vr1841fsqUKZQvX14Sy0IIIYQQQgghhPhHkSyS+Ed6//336dy5MxcvXlTGUlJS+Omnn1iwYIHF/ISEBIsK6D/jm2++YerUqRQrVgwXFxcmTZrEihUrcHZ25uuvv8bV1ZWNGzdaxN27d48rV67wxx9/8PPPP1O6dGl0Oh0GgwEHBwe+//571q1bp7TBOHjwINWrV0etzv4n6OXlxYwZM2jZsiX9+/fPtxf1k/r27Uvbtm1p27YtgYGBNGrUiGHDhrFu3bo/lYQ/OG0BTs5OhY77L9m/50em7T/Fjm07sLe35/LFi8yfNhMvT8uNE3NERETQtGlTBg4cCEBISAhr1qxhxowZXLlyhZCQEIKDg/nll18sYmNiYli6dCmnT59+ac8khBDi/7F35+ExXv//x5+TmSRDRHZLLBFrLRVbCFqxE2opqtbaQpUQaxctxYcoSosGJUhRQqPW2qq2Vi0REYJaIvYtIXvMJJmZ3x/55f4aWYRqLX0/rmuuuu9zzn2fM8ofrxzvI4QQQgghhHgWEi6LFyYtLS3PUg4uLi64uLgQFRWFwWAA4IsvvqBVq1aUKlUKyCpFkZ6eDmTVIz506BDOzs4kJyeb1RNOSkoiPT2dO3fumL3DaDSSkZGBm5ub8o4pU6Yo7Vqtlt9++025fvjwIX/99Rd3795FrVYDsG/fPiZNmkShQoXo0qULffr04ezZsyQnJ1O3bl2MRiOXL18mNTWVsmXLsnPnTtq2bcvSpUvNwt/4+HiMRiMpKSl89tln9OrVi2PHjlGtWjWKFStGoUKFlL7p6enKfLOv+/Xrx/jx4wHo27cvlStXJi0tzazMRkHUcq9A0aJPLvHwX7b17hoaN2pE4+o1AajtXpFhffvnOyYyMhIfHx/lun79+kydOhUAJycnwsLC2LRpU45w2WQyMWTIEBo1asThw4fR6XR4eHg83wUJIYQQQgghhBBCPCMJl8W/LjU1ldatW3P8+HEGDRqUb1+dTodOp+PSpUvs3r3brB5t2bJlAXjzzTdxdXWlUqVKBAQEMGXKFKysrHI8q2LFimbXBoOBokWLcvfuXRITE5847+vXr9OpUycaNWpErVq1MBqNzJo1i/nz59O5c2fOnz9PcHAws2fPJiYmhuTkZPR6PZmZmRiNRlQqFSNGjKBVq1ao1WoGDhzIhAkTCA0NRa1W07p1a1auXEnFihXZvHkzixcv5tixY9y5c4cNGzbQpUsXIKtWdXp6OmfOnKF79+6UL18eHx8fLl++jK2tLb/++ivLly/nzz//ZMmSJdStW/eJa8t2MiZadi4/xtnWzmxXclJSEu7u7sq1SqVCrVYTHx+Pg4NDrs94fEzRokW5desWQJ5jIGsn/bFjx+jVqxfnz59nwoQJjB49WvlBghBCCCGEEEIIIcSLpDKZTKYXPQnx37Nx40aKFClCs2bNlNIQT2IwGJQdwy8Lo9Fodkjh03rw4AEajUbZLfzjjz/yySefcOPGDbM+9vb2Zu+xt7fn4MGDF4SN2wABAABJREFU1KxZM8czGzVqxPjx43n33XcLPI+kpCTs7OygY1OpufwYrZUV5+etUALmTz75hIyMDLPyLGXKlOHIkSPKrvrHNWjQgM8//1zZrR4dHU3btm25ePGi0ic4OJjg4GCzcijNmzfH2dmZ9evXA3Do0CGaN29OXFwctra2z3upQgghhBBCCCGEEMD/ZUWJiYn5/it3SZHEC/E0wWe2ly1YBv5WsAzg6Ohodh0dHU3Dhg3z7QNgbW2dZ7ioVqvRarXPNiE3D7BzeraxryNdCrqYE8QlJyrhsqOjI1FRUWbdkpOTc90tn83R0ZHY2NgC989248YN+vfvr1zXqVOH9PR0rl+/TrVq1Z5yMUIIIYQQQgghhBDPl4TLQrwg169fp2zZssohf5BVe7lIkSJmhxM+ePCAM2fOUKVKFXQ6HdbW1qhUKkwmEzqdLkeQrFar86xl/URaG7Cxf7ax/xGenp4sXbpUuY6JiUGv1+f6Q4BHxxw+fFgpAxMREZHnLudHlS5dmocPHyrXV69eRaVSUbJkyb+xAiGEEEIIIYQQQojnQ8JlIV6Q7HIgcXFxQFbg6OnpSXR0tFm4XKJECSwtLYmJiaFGjRpYWVmRlJREnTp1aNy4MS4uLvz6669KoBwbG0vv3r0BuHfvXq47vvV6PXq9XrlOSkr6x9b5umnSpAlJSUmsWLGCAQMGEBAQQMuWLVGr1SQkJGBra5vjO+/atSuNGzfG398fd3d35s+fT58+fZ74rp49ezJz5kxq166Ng4MDI0eOxMfHJ986zUIIIYQQQgghhBD/FgmXhXhBihYtytq1a4GsetL+/v4YjUZOnjxJy5YtlX6rV6+mePHi2Nra8vDhQ/bu3UuLFi04efIk5cqV48GDB1hbWyuBZuvWrRkzZgz169fPs5TIjBkzmDJlyj+/yNeQRqMhKCiInj17Mn78eCwsLJQ6yQ4ODkRERFCrVi2zMR4eHvj7+1OvXj20Wi2VKlVi2LBhT3yXr68vcXFxvPfee8TGxvL222+zbNmyf2BVQgghhBBCCCGEEE9PDvQT4iUwdOhQjh49ygcffMD+/fvZvHkzJpOJPn36MHLkSBo0aKD07dq1Kz///DM9evRg0KBBtGjRgq1bt+Lj44OlpSVNmzbl008/pW3btnm+L7edy2XKlIHxE8CxxD+61ldKagKcO0j4rIXUKV/JrOnOnTuEh4fj5eVlVtokP2fPnuXmzZt4e3sXqOayEEIIIYQQQgghxIsgB/oJ8Yr49NNP+f7774mOjqZkyZLMmDGDffv2sWbNGk6fPm1WmzcsLIwjR47g4OCApaUlQ4YM4fTp03z55ZdcunSJMWPGFOid1tbWWFtb/1NL+k8oUaIE7du3f6ox1apVk4P4hBBCCCGEEEII8dqweNETEOK/KjY2li5duhAcHAxA+fLlKVSoENOnT8fHx4cLFy7w+++/U7p0aQDS0tIYPHgwY8eOxcrKis8//5xOnTqh1+vx9/dXSmwIIYQQQgghhBBCCPFvkJ3LQrwAly5dokGDBnh7e3Pw4EGqVKmitA0ePJjQ0FCKFi1KkSJFlPvfffcdGRkZ+Pn5MWvWLKytrfnmm2+ArIPfsg/x+1t0qVmlIF5X9+7C1o0Q/wBq1YUWreH/H4SYK10K3LhL+7ebojKZmDNnDj179jTrEhoaSmBgIPv27VPuGQwG/Pz8+PHHH8nMzKR3794sWrRIOcRRCCGEEEIIIYQQ4nUgSYcQL0DFihU5dOgQb7zxBnFxccr9DRs2UK9ePdatW0fLli3x8fFhxYoVlCpVilGjRtG1a9dca/U+txIXVyPB8jX9a8FghN1/QnEn8K4DkX/Bzngo55r3mMQUCDvDqK9n065lK7p06UKdOnWUHwbs2rWLfv364enpaTbsq6++IiIigiNHjpCenk7r1q2pX78+gwcP/idXKIQQQgghhBBCCPGvek1TJPEqmD59Ot27d6dSpUpP7vwUTCYTqlx2oy5YsID+/ftja2v7XN9XUBkZGVhaWirXb7zxBgBGoxGAgQMH8vPPP7Np0yaaNm3Knj176N69O2+88QajR49m6tSpVKhQgYyMDDIzM80O5AOIi4sjMjKSCxcuYGNj80xzPDB1LkVsizy54yto3+5fmbovnO1bt1OoUCEunDvHV19OYfmshXmO+fp/07nlXYhPRmfVsvbz82PVqlVMmzaNS5cu4efnx/Dhwzl27JjZuLi4ONasWUP58uUB8PHxISIi4p9bnBBCCCGEEEIIIcQLIOGyeCHOnTvH7NmzGTRo0BP7tmvXjvHjx9OsWTMArl69Srly5UhJSck1RP3oo48wGAx88803ZmUlIiIiiI6O5ttvv83zXU2bNiUhIQF7e/scbTqdjlu3bnHt2rUnL/Axy5cv59dff821LvLvv/8OZJ3CefbsWVxds3bS2tvbs2vXLhYvXqwE8Onp6TRo0ACdTkdSUpLZc9LS0ujduzetW7fOsZP2v8bZ1o6yLsXM7m29u4bGjRrRuHpNAGq7V2RY3/7UKZ/3DzduX7lKOx8f5bp+/fpMnToVACcnJ8LCwti0aVOOcDm7XEm28+fP8/777/+tNQkhhBBCCCGEEEK8bCRcFv+KqlWr8uDBAwoVKgTA/fv3sbCwwMvLi7S0NLRaLRYWFjx8+BAvLy82b94MwMWLF4mMjMTLy0t5VvYzsv/7uIkTJ9KjRw98fX25desWUVFR2NjYkJGRwcOHD9m0aROQFcZ27tyZJUuWKGOtra0xGAxkZmbmeK7BYMjznfnZsGEDy5YtY9u2bQBcuXIFd3d3unTpwoYNG2jatCmQtdvV1dXVbNd16dKl8fPzo2XLlgBYWVkRHBxM9+7dcXJyMntP2bJluXPnzlPP71Hek8a8FmUxtFZWnJ+3wixgTkpKwt3dXblWqVSo1Wri4+NxcHDI9TmPjylatCi3bt0CyHPM4/bt20dUVBRbt259lqUIIYQQQgghhBBCvLRe/RRJvBLOnTun/HrevHls2bKF7du3Y21tzcSJE7lw4QJr167FwsLCbFxwcDCxsbGULFkSABcXFw4fPgyQo2+2UqVK8euvvyqhoVarZdq0aZw9e5Y1a9aQmZmZ58FqBoOBjz76iDp16uRou337NuPGjXuqdd+5c4cvvviC/fv35wgjz549C8Dly5dzjDt48CBvvvkmZ86c4Z133sHT05PmzZsD4OHhwcKFC+nTpw9//vnnU83nidw8wM7pyf1eZroUdDEniEtONAuXNRpNjtrUWq2WtLS0PIPix8dk9y+o1NRUBg8ezJdffomLi8tTLkQIIYQQQgghhBDi5SbhsvhXzZ8/nzFjxlCuXDnq1q2r3D979iyxsbF88803eHh4ABAfH8+KFSu4fv06xYsXZ/Xq1SxfvlwZ89NPP2Fra0vbtm2Vew8fPuTXX3+lY8eOSiB9/fp1Fi5cyG+//QZA165d6dGjBz179swxv969e3P16lV27tyZ6/yHDx/+VOtdtGgRw4cPp3jx4jnarly5Qnp6OlFRUajVarM2W1tb7O3tady4MZ6enoSHhyvhMkCLFi2UNbVo0eKp5pQvrQ3Y2D+/571EHB0diYqKMruXnJyc6wGJj46JjY0tcP/H+fn5UbZsWcaOHfv0ExZCCCGEEEIIIYR4yUm4LP4VUVFRfPLJJ9y+fRt3d3cuXbqUo8/cuXOpX78+VapUYevWrXz++ecMGjSIYsWydp8ePnyYt956S+lvZ2dHz549OXjwINWrVwfg0KFDdO/enYEDBzJ37lxMJhM9evRg1qxZvPHGGzx8+JABAwbQq1cv3NzcaNSoEQAjRozg0KFD2NvbU7hw4TzXkZmZSUhICN7e3syePfuJ6/7ll1/yDKo9PDw4f/48Z86cybNG8uXLlwkPD881nOzRowfbtm17pnBZr9ebHQj4eP3m15GnpydLly5VrmNiYtDr9Tg6OuY75vDhw0pt8IiICEqVKlWg9y1cuJDdu3dz4sSJPHfZCyGEEEIIIYQQQrzKJFwW/7jExES6detGp06dCAwMpEKFCjkOzNPr9Xz33XdER0fz+++/s3v3bk6dOkXbtm1p3749q1evZuPGjWzcuFEZ07p1az7//HM6d+5MWFgY9vb2tGzZklOnTtGjRw9OnDjB9u3bOXLkCNeuXWP69Ok4Ojri5OREx44d6datG8ePH8fV1ZUFCxYAsGLFChITE/Nci0qlwt/fv8Brf/DgAc7Ozrm21axZkzNnzhAVFUXNmjU5f/680vb222+jVqtJTEzkww8/pE2bNjnGu7m5sW7dugLP5VEzZsxgypQpzzT2VdWkSROSkpJYsWIFAwYMICAggJYtW6JWq0lISMDW1jbHDvKuXbvSuHFj/P39cXd3Z/78+fTp0+eJ79q3bx9jxoxh27Zt2NjYkJKSglqtfqaa3UIIIYQQQgghhBAvKwmXxT/Ozs6OiIgIChUqxI0bN3LduZycnIxaraZw4cL07NmTjIwM2rVrh4uLC3v27OGNN97AxcWFBg0aEBcXp4wbM2YMBw8eZPDgwfz0008AVK5cmX379mEymahXrx5Vq1alfPnyXLp0iUqVKgFZu1b9/f1zlKv46quvGDJkCBUqVADggw8+YMmSJWi1WpKTkxkyZMhThcvW1takp6fnWkohO1w+d+4c77zzjlm4vG7dOt544w3CwsIYOnQoHTp0oH379mbjk5KSsLOzK/BcHvXZZ58xZswYs2eVKVPmmZ71qtBoNAQFBdGzZ0/Gjx+PhYUF+/fvB7IO54uIiKBWrVpmYzw8PPD396devXpotVoqVarEsGHDnviu+fPno9fradWqlXLP29tbeZ8QQgghhBBCCCHE60DCZfGveHTH5tWrVylXrpxZu16v54svvlBqGltaWirlBxYtWkSpUqWYPHlyrs9evHgxy5cvx2QyoVKplDF//PEH27ZtY+PGjbRo0YL9+/fTtm1bjEYjv//+O8HBwTmeZWFhQXBwMDY2NkBWDee5c+diYWFBZmbmU5c3qFy5MseOHTMr55GtZs2aTJkyBUtLS4oUKWLW5urqSvny5Slfvjx//PEHS5cuzREuHzlyhGrVqj3VfLJZW1vnONzuv6Bjx45ER0cTHh6Ol5cXTk5ZhxeaTKY8x0yfPp3evXtz8+ZNvL29c/ygoH///vTv39/s3qM77IUQQgghhBBCCCFeVxIui3/Fw4cPlVDOzc0t15rLkFXTWK/XK+EuwMiRI/H29ua9997LdUyJEiWYMGGCcp2ens6CBQsICgoCQKfTUapUKVQqFSqVCrVajUaT+//6Xl5eODg4KHWXT506RbNmzbC0tCQzMzPXg/ny06dPH+bMmZNnuLx37146d+6c7zOMRiMGg8HsXmpqKkFBQRw6dOip5iOy/n95PKh/kmrVqj1zkC+EEEIIIYQQQgjxupJwWfwr2rZty6VLl1Cr1aSmpmJlZYWrq6vSnpiYiJ2dnVJC4sqVK2RmZjJy5EiOHDnyVCHqsmXLKFWqFD4+PhgMBiIiInjzzTdz7ZuWlqYEyUeOHCEyMtJsZ2pGRgb79u1Tdiynp6dz6NAhGjduXKC5dO3ale+++46goCB8fX3N2uzt7SlTpgw1a9bMMS45OZm4uDjCw8NZs2YNn332mVn70KFD6d27d4EPlyswXSqkJjzfZ/7bdCk5bkVFRTFgwAAuXbqEr68vs2bNUna55yU0NJSxY8eSkZHBnDlz6NmzZ472wMBA9u3bp9wzGAz4+fnx448/kpmZSe/evVm0aFGeP8wQQgghhBBCCCGEeJVJ4iH+FQcOHADg+vXr9OzZky+//JJWrVphMpm4d+8eLVq0oGPHjkqZiJMnT/LRRx+RkZHB3r17KVq0qPKsjIwMIGuX8+Oh3a1bt/jiiy9YtmwZAAsWLKBkyZK4u7tjNBoxmUxYWFig0+nIyMigYsWKnDhxghIlSuDh4cGuXbtwdnZWgkdnZ2f27t1LkSJFMJlMpKWl5Vo/OS8WFhasXr2aVq1aYTQaGTJkiFm7h4cHNWvWJDk52ex+kyZNUKlUuLq6MmTIEEaNGgVk7WLu378/CQkJLF++vMDzKLCrkWD56v+1oLWywtk2qx61Xq+nQ4cOtGnThpCQEEaOHElwcDADBgzIc3xUVBS9e/cmMDCQBg0a0KVLF+rUqUOVKlUA2LVrF/369cPT09Ns3FdffUVERARHjhwhPT2d1q1bU79+fQYPHvzPLVYIIYQQQgghhBDiBVGZ8is2KsRztGvXLjp27IhWq6VQoUJkZGSg1WpxcHDA1taW+/fv4+DgwP79+3n48CGBgYGMHz8erVZr9pwrV67g7u5OcnJyjlrF586d49tvv2Xx4sXMmzePgIAA9uzZQ82aNenUqRNt27alTp06tGjRAktLSzw9Pdm9ezfbt29n0qRJ2NnZme1ojYyM5M033zSrtZyUlMTgwYOfKjCMjY0lIiKC1q1bP+O393/Wrl1L9+7dUavVf/tZ2bIPBzxw8gRFbIs8ecBLztnWjrIuxQDYtGkTAwcO5MaNGxQuXJjIyEiGDx/OH3/8kef4UaNG8ddff7Fz504A5s2bR2xsLNOmTePSpUv4+Pjw7rvvcuzYMbND+kaPHs2IESMoX748AP369cPGxoaFCxf+c4sVQgghhBBCCCGEeM6ys6LExESzTZ+Pk3BZ/GtSUlLYsGED5cqVo1y5cpQuXdosINXr9Rw7doy33377ubzv7t27pKamKkHfs3r0oMB/2q5du6hYsSIVKlT4V96X7XUJlx8NlbNNmTKFo0ePsn37diDr99PJyYkHDx7k+ZxmzZrh4+PDxx9/DMDhw4eZOnUqO3bsID4+HpVKxaZNmwgODjYLlx/n5eXF+++/z+jRo//+4oQQQgghhBBCCCH+JQUNl1/9f/8uXhlFihShX79+ebZbW1s/l2A5MzOTq1evotVqKVy4MHfu3Mm3r16vp0KFCmRkZKDRaJg5cybR0dEsXbqUjIwMjhw5wsiRIzlx4gT+/v6MHDmSihUrKs8ICQmhYcOGlC1bFp1Oh1arRaVSceTIET7++GMOHjwIZJXzMBqNWFtb5zmf77//HmdnZ5YsWZLvGjUaDXFxcdjb29OmTRuuX7+u1I6GrN3ds2bNYuDAgQX92gDwnjTmlS6LobWy4vy8FWYBc1JSEu7u7sp19qGO8fHxODg45Pqcx8cULVqUW7duAeQ55nH79u0jKiqKrVu3PstShBBCCCGEEEIIIV56r26KJEQe7ty5Q5UqVdBqtWY1mRMTE7G1tTUrcWE0GsnIyODhw4d07NiRq1evEh8fj16v588//0Sr1bJs2TIsLCxQqVQ0atSIvn378ueffyq7mf/880+2b9/O9OnT8fT0xNraGpVKRXp6OvHx8ZQrVw7ICrIHDx7Ml19+CcDs2bP5+uuvKVSokDIfvV5PRkYGu3fvBrIOEExKSiIlxfyQukKFCnH58mU8PDxylA3Jltf9fLl5gJ3T0497GehS0MWcIC450Sxc1mg0OQJ9rVZLWlpankHx42Oy+xdUamqq8nvt4uLylAsRQgghhBBCCCGEeDVIuCxeO6VLlyYzM9PsXmZmJpaWlpw6dUoJex+VkZHBtm3bUKvVfPvtt/z1118sXrwYgOjoaKVfjx496NSpE3q9XgmRe/XqxTvvvMPixYvNdkmfPHmScePGsWfPnlznaTQaef/995k/fz7p6emsWbOGPn36oNFo0Ov1LF26lA8//BBLS0tlzLFjx7h27RpqtZoRI0bw5ZdfYjQa8fPzo3Llykq/2bNn80wVb7Q2YGP/9ONeYo6OjkRFRZndS05OzvdgRkdHR2JjYwvc/3F+fn6ULVuWsWPHPv2EhRBCCCGEEEIIIV4REi4LAUyfPp21a9diaWmpBMc1atQAsmr0Xrx4Ubk2Go3o9XqOHDmCi4sL9evXJyYmhsKFCzN58mS+/fZb7O3tc+xcvnr1ao5DCFUqFQ8fPsRgMDBgwAA++OADAAwGAyNGjGDw4MFKqQ2A7du3c//+fSAr6F6/fj0tW7bk1KlTnDp1Snmuu7t7riH6f5GnpydLly5VrmNiYtDr9Tg6OuY75vDhwwwaNAiAiIgISpUqVaD3LVy4kN27d3PixAmzXfJCCCGEEEIIIYQQrxsJl8V/zu3btylRooTZIX2TJk1SDm+rVasW//vf/+jUqRM6nQ5ra2tcXFyIiori1q1b3Lp1i3r16gHw22+/ce/ePaysrOjatStWVlaMGjWKyZMnm+1czt45/WipBZPJhFqtpkWLFiQlJQFQp04dpQ2yQk69Xk9YWBhFixbl2LFjDBo0iFWrVtG1a1fOnj3LqlWrcl3n8ePH+d///oePj0+ONr1ej16vV66z3/86atKkCUlJSaxYsYIBAwYQEBBAy5YtUavVJCQkYGtra3awJEDXrl1p3Lgx/v7+uLu7M3/+fPr06fPEd+3bt48xY8awbds2bGxsSElJQa1Wm5U+EUIIIYQQQgghhHhdyLY68Z/ToUMH+vbtS3p6unLv6tWrVKpUCUdHR+Lj4xk9ejTlypXD3d2da9eu4ejoyL179wgJCWH06NHKuNjYWCIjIxk8eDCQVSN54cKF1KhRg27dunHkyBFq1KhBrVq1lPZsOp0OS0tL/vzzT44dOwZAaGgooaGhrF27FsgqrXH+/HmKFi2KyWTizp07eHt7A1mlG3Q6HV9//TWjRo3inXfeYdOmTRQpUoTjx49Tr149kpOTc/0OZsyYgZ2dnfIpU6bM8/uCXzIajYagoCD8/PxwdnZm8+bNzJw5E8g6nO/06dM5xnh4eODv70+9evUoVaoUarWaYcOGPfFd8+fPR6/X06pVK2xtbbG1tc013BdCCCGEEEIIIYR4HahMz1SYVYhXS/bO4ZiYGABatWpFhQoV2LRpk1JyYtu2bcycOZMff/wRX19f5VA9yNrJ+tFHH/G///2PcePG0aFDB6XtypUrNGjQgLt37yr3goODGT16NHXr1qV379507dqVokWLms1p/PjxuLi48PHHH/Pw4UPGjx+fY95z587Ntdavvb09d+7cYeDAgYSHh5ORkYFOp8PFxYXLly9TpUoVrl27xjfffEPv3r1zjM9t53KZMmVg/ARwLFHQr/XlkpoA5w4SPmshdcpXytF8584dwsPD8fLywsmpYIcWnj17lps3b+Lt7f1UNZeFEEIIIYQQQgghXmVJSUnY2dmRmJiYI9N6lITL4j/h0XC5XLly3Lp1i2bNmlGuXDk2b96MVqulWrVqpKWlUahQIS5evEilSpVQqVScPXuWBQsWsGXLFm7cuMHZs2fNSmpcuXIFLy8v5TC/Y8eO0alTJ7755huWLl2Km5sbR48eZcuWLVSoUEEZ17dvX9q0acOZM2dYv349RqMROzs7pT0lJYV3332X2bNn51hPdrhsZWWllO54vLTD08j+C+N1DpeFEEIIIYQQQgghRMEUNFyWshjiP8nV1ZVff/2VsmXLKvWNDx48yLlz5zh8+DD29vacPn2a3bt3k5GRwbvvvsuePXuYMmWKWbD8KJPJxI8//ki7du1YtmwZlSpVwmQysXz5cnr27EmDBg04evSo0v/SpUuULl2aGTNmcP78eVxcXPjqq684efIkixcvJjMzk08//TTfdVy8eJGaNWui1Wrx8vJSPhqNRqkh/VR0qVkh7av40aXkuqSoqCg8PT1xcHBg/PjxFOTnaaGhobi5ueHq6qqUKHm8vVmzZnmOzatNCCGEEEIIIYQQ4nUiB/qJ/6yyZcuydOlSAC5cuMCGDRuIi4vj+vXrxMfH88Ybb+Do6MjBgwf59ttv0Wq1XLp0CZPJxLJly+jXrx+WlpZAVv3k6Ohofv31V37++WeaNGnCkSNHMBgMAHzxxRe88cYbVK1aFcj66c/JkyepW7cukFUXeOXKlbRp04YxY8Ywb9481q9f/8TyDVWqVOHixYt8+OGHGAwGJk6cyBdffMHbb7/NrFmznv5LuRoJlq/uXwtaKyucbf9v97der6dDhw60adOGkJAQRo4cSXBwMAMGDMjzGVFRUfTu3ZvAwEAaNGhAly5dqFOnDlWqVAFg165d9OvXD09Pzxxj82sTQgghhBBCCCGEeN28uimSEE/BaDQC5LlrVavVcvXqVWrXro23tzd79uzh0qVLpKWlMWLECKKiojh16hTNmjXDaDQSFBTEwIEDuXr1Kr169cLFxYW33nqL9957Tznkz9LSkiFDhnDlyhXS0tIoWbIku3fvpmPHjgQHB/PWW29ha2sLZIWg169fx83NjdGjR1O/fn0uX76MnZ0dJUuWzPHPD9LT05XgOi0tjQ4dOjBq1Cg2bdrEm2++yZAhQ3jw4AGOjo5P9T0dmDqXIrZFnvbrfWk429pR1qWYcr1jxw4SExOZO3cuhQsXJiAggOHDh+cbLgcFBdGsWTN8fX0B8PPzY9WqVUybNo1Lly7h5+fH8OHDlUMYs+XXJoQQQgghhBBCCPE6knBZvLZMJpNSwiL78DqdTpdr37Jly7J48WIAbt68SXp6OgBfffUVBoOBPXv2YGNjQ1BQEJ06dWLFihVYWFiwcuVKGjZsyJw5c4iLi2PlypWsXLmSCxcuEB8fj06nIyMjQwm1PTw86NatGykpKQwbNoyffvqJ//3vfyQnJ+Pl5cWHH36Ir68v1tbWbN++nUmTJnHp0iWGDx/OggULlPnq9XqSkpJo27YtGo2Gpk2bsmPHDipVqsTRo0fZtm0bkyZN4r333mP48OH/2Hf8Mnk8WAaIjIzEy8uLwoULA1CzZk3Onj2b73MiIyPx8fFRruvXr8/UqVMBcHJyIiwsjE2bNuUIkPNrE0IIIYQQQgghhHgdSbgsXgmLFy9m+fLlOUK7N954gwULFtCqVascY9q0acMHH3xAnz59sLW1JSEhAXt7ezIzM/M9/K5UqVKkpGTV780OFbO1bduWuLg4ZcfxxIkTWb9+PSdPnqRWrVr4+/szfPhwLC0tSUlJwc7OjocPH2JtbU1GRoYSdk+YMIE2bdpQp04dduzYQalSpYCs3a/e3t5MmjSJH374Acjamfz4juvsXcu///47AF9++SU1atRQQtTMzEyKFSv21MGy96Qxr2xZDK2VFefnrTALmJOSknB3d1euVSoVarWa+Ph4HBwccn3O42OKFi3KrVu3APIc86Q2IYQQQgghhBBCiNfRq5kiif+Mb775hsWLF5OSkkJCQgI1atQwa798+TK+vr6oVCq+++473nnnHQBu3LjB77//TlBQEOnp6Wg0GmxtbVGr1fkGywWRHSxnK1euHB07dmT9+vUYDAZGjhyJRqNRAuGmTZtiMpkwGAyMHj2a3r17A7Bw4ULatWtHkSJFGD9+PGq1mooVK7J161Y2bNigPF+j0WBlZQXA3Llz+fTTTylcuDAmkwmtVsvdu3exsrKiV69eBAcHA7B//36GDRv29Itz8wC7/Os8v5R0KehiThCXnGgWLms0Gqytrc26arVa0tLS8gyDHx+T3V8IIYQQQgghhBBCmJNwWbzURo8ezejRowkKCmL16tXs37/frL1cuXIEBQXRsmVLs/vfffcdvXv3pmzZstSuXZsZM2bQtm1bsz4RERHUrl37b8+xfv36LF68mAMHDvDJJ5/w3nvvKWFyWFgYnTt3xmQykZmZSYcOHZRxFSpUYO/evVhaWtK/f39+/vlnChcuTEZGBgaDge+//5709HQePnxIfHw8RYoUwdLSUgmR79y5Q7169QCU8PlRFhYWT78YrQ3Y2D/rV/HScXR0JCoqyuxecnJyrt/Xo2NiY2ML3F8IIYQQQgghhBDiv0rCZfHaSUxMZMmSJQQEBABgaWmp7EQ1mUxMmjSJH3/8kbS0NG7fvv1c3tmuXTvatWsHgLe3N2q1mszMTCZOnEjLli0xGo1kZmai1WoBePjwIZcuXeLNN98EYM2aNcqzvv76a6KiopRdyI+ytLQ0u9Zosv4Iq1QqTp48yeTJkwG4cuXKc1nXq87T05OlS5cq1zExMej1+nwPOvT09OTw4cMMGjQIyPohRHbZEiGEEEIIIYQQQgjxfyRcFq+M8PBwZaduttzC4VmzZpGYmGh2b9myZXz88cfKDuKZM2cyatSovz0nHx8foqKicHBw4NSpUwwePJgTJ05gZWWFSqXCyckJf39/TCYTGRkZWFlZcejQIQ4cOEC3bt345JNP+Oyzz5SQuCBCQ0PZv38/BoPBrMSHg4ODUjZEpVJx/PjxPJ+h1+uVQw4hq87w66hJkyYkJSWxYsUKBgwYQEBAAC1btkStVpOQkKCUSnlU165dady4Mf7+/ri7uzN//nz69OnzglYghBBCCCGEEEII8fKScFm8MurWrZtrWYxHRUZGsnjxYrp168bvv//OggUL+Ouvv6hXrx6rV6+mevXqBAQEEBkZ+bdrLwNs3bqVuLg4JfReunQp+/fv56+//srRt3z58rRu3RrIOhjw4MGDDBkyhA8//BBnZ2cMBkOOnckA6enpZmUZunXrppTF8PLyArIO8HNzc6Nbt24AODs789NPP+U57xkzZjBlypRnX/grQqPREBQURM+ePRk/fjwWFhbK/0MODg5ERERQq1YtszEeHh74+/tTr149tFotlSpVerb61UIIIYQQQgghhBCvOQmXxSsjLCwsx4F+t27dMrt2cXFh/vz5hIWFUbx4ccaOHcuwYcPo3r07VapUUfplZmY+1W7hvGQ/49FnrV27ltTUVOVwQYA9e/Zw4MABJVwGqFOnjrK7eNeuXXTo0AEbGxvS09MxGAxs27aNhw8fUrFiRSIjI/Odh16vZ/fu3Urt6fj4+Hz7f/bZZ4wZM0a5TkpKokyZMgVc9aulY8eOREdHEx4ejpeXF05OWQcWZh+4mJvp06fTu3dvbt68ibe3d46ay/3796d///65js2vTQghhBBCCCGEEOJ1IuGyeGkZjUZMJpOyw9jT0zPPnctGo5GMjAxcXV3p3bs3YWFhODg4UKdOnRzPXbNmDYsXL84RVD8vGo2GAwcOmO1ejo2NpVmzZjn6bty4kdjYWIYMGUJ6ejqQf81lgJUrV7J69WoASpcuDWTVmf7www/58ssvAdi/fz9+fn55ztHa2lqpQ/1fUKJECdq3b/9UY6pVq0a1atX+oRkJIYQQQgghhBBCvPosXvQEhMhLWFgYDRs2pHHjxgQHB5OZmclbb71l9ildujSTJ0/m7bffpnHjxiQkJOT5vOydqlWrVqVfv36sXLnSrD09PZ24uDhSUlKeab4XL15k2bJlqFQq/P39OX78uPL57LPPcvQ3Go1MmjTpqXZQm0wmPvjgAzIzM7lx4wZGoxGAqKgo3njjjWeatxldKqQmvHofXc7fs6ioKDw9PXFwcGD8+PH57lTOFhoaipubG66urqxduzbX9tx+SPCkNiGEEEIIIYQQQojXkexcFi+tBg0acOzYMQDu3LnDiBEjmDdvHq6urgDs3r2btWvX8s0332Bvb//E52VmZlKpUiU8PDyoXbs2V69eJSQkhEGDBqHRaNiyZQvvvfce/fr1y3PXcG4yMjJISkqiXbt2jBs3DoB58+YREhKi9Mlt5/LatWvJyMigX79+BX6XwWBQfm1lZUW9evVIT08nPDycFStWFPg5eboaCZav5l8LWisrnG3tgKwyIR06dKBNmzaEhIQwcuRIgoODGTBgQJ7jo6Ki6N27N4GBgTRo0IAuXbpQp04dpZzKrl276NevH56enjnG5tcmhBBCCCGEEEII8bp6NVMk8Z9y8OBBevXqRadOnXB0dFTuV69endjYWGrUqMHKlStp3ry50mY0GpUg1tLSkitXrtC0aVPOnTun9Pnll1+YPn06gwcP/lvz27p1KyqVimXLltGkSROGDh2Kv7+/EjQDLF68mCNHjijXiYmJfPzxx8ycOROVSoXBYMjzgMHMzEyMRiNWVlY0aNAAd3d3ABwdHfn5558JDQ2lbNmylCpVymycSqV66rUcmDqXIrZFnnrcy8DZ1o6yLsUA2LFjB4mJicydO5fChQsTEBDA8OHD8w2Xg4KCaNasGb6+vgD4+fmxatUqpk2bxqVLl/Dz82P48OHKDzyy5dcmhBBCCCGEEEII8TqTcFm81ObMmcOMGTNYunQp7777rllbqVKl2LZtGwsWLKBdu3b88ccf1KtXD8jauZqUlATAoEGD+Oyzzxg1apTZeFtbW+bMmYOFRVZ1mG7durFgwQJu3rz5VHPs168fzZo1o2rVqkDWTuZHnTt3jsmTJzN+/Hjl3syZM7G2tqZnz578/vvvtG7dGisrK9RqNSaTCZPJxKZNm8jIyCA9PZ0OHTrw888/59gZm5qayhdffMHw4cOVe4GBgaxfv145uO5p1HKvQNGiRZ963MsmMjISLy8vChcuDEDNmjU5e/bsE8f4+Pgo1/Xr12fq1KkAODk5ERYWxqZNm3IEyPm1CSGEEEIIIYQQQrzOJFwWL7WePXvSrVs33Nzc8uwzYsQIWrdurZQvAPj++++VX/fv35/+/fs/8V3x8fEsX76cLVu2PNUcbWxsqFq1KkeOHOHNN99k2bJlZu1Vq1bl6tWrZgfoTZkyhW7dutGvXz98fX3R6/VKm8FgoEWLFkyePJmmTZvm++6bN2/i7u7OoEGDlHtly5alYcOGyg7cp3EyJvqV27n86I7lbElJScoOb8jaxa1Wq4mPj8fBwSHX5zw+pmjRoty6dQsgzzFPahNCCCGEEEIIIYR4nUm4LF5qrq6umEwmMjMz0el0JCUl8eDBA+7du8etW7e4ePEi4eHh1KlTR9llChAcHMz8+fM5ceJEgd/l4ODAkSNHsLKyUu6VLl2anTt3UqNGjSeOHzhwIAMHDjQrhwHw6aefcu3aNdasWaPc02g0VKhQgZ9++kmZt9FoJCEhAa1Wy/vvv89vv/2Gl5cXer0eCwsLbG1tAbhx4wY1atQgISGBypUrc/nyZRo1amR2MOD58+dp3bo1FStWLPD6AbwnjXnlai5rraw4P2+FWcCs0WjMwnwArVZLWlpanmHw42Oy+wshhBBCCCGEEEKI3L1aKZL4z0lPT8fd3Z3Y2FhsbW0pWrQo6enp6PV6fHx8KFGiBM2aNaNMmTJm4woVKqSEsQCrV69mwIAB2NjYYDAY0Gq1xMbGmo3R6XRYWlqa3dNqtWi12hxzUqvVZjWST5w4we3btxk6dGiONWi12hwHDvr4+HD06FFMJhPe3t6kpqby3XffMXHiRDQajVIv+aeffsJoNPLee+8xffp0ZW3W1tZERUVRo0aNHPN79L1Pzc0D7J6+nMYLo0tBF3OCuOREs3DZ0dGRqKgos67JyclmPzh4nKOjo9n/E0/qL4QQQgghhBBCCPFfJ+GyeKlZWVlx7do1syA3KCiI1atXs2rVqhz9DQYDRqMRtVqNSqXCZDKRkZGBVqvFx8eHLVu2cPz48Rz1mwHc3NxITU012wGcnJxMnTp1lLrMJpOJ9PR0fvzxR7p06aL0mzVrFn379qVIkdxLSmSPz7Zz504GDBhA1apV+fjjj5X7vXr1YtWqVXTo0AF7e3tWr15N69atKVYsKzjdtWsXKSkpqFQqOnfuzPbt2zEajUyZMsWsVvLYsWMxmUz5fre50tqAjf3Tj3vJeHp6snTpUuU6JiYGvV5vdiBkbmMOHz6slBiJiIjIcUiiEEIIIYQQQgghhPg/Fk/uIsSLlZ6enuOQvEcZjUZSU1MB+PnnnylRogS+vr4cOXKEsmXL0rt3byVszvZoWJ3t7t27pKSkkJCQoHwqVarEqVOnlOvExEQePnxoFixHRkYSGhqKo6Mjo0aNokiRItjb2yufr776iqVLl2JnZ6eE2unp6fzyyy/Ur1+fN998U3nWhg0bGDp0KNHR0RiNRkJDQ2nTpg2JiYkArF27lpMnTwLw/vvvs379et599112795NaGio8mnYsGG+B/plH3j46Od10qRJE5KSklixYgUAAQEBtGzZErVaTUJCAgaDIceYrl27EhISwunTp0lJSWH+/Pm0adPm3566EEIIIYQQQgghxCtDwmXx0mvTpg1OTk44Ozvj7OzM6NGjOXTokHLt5OSEk5MTer2e9957j/v379O8eXO8vLy4fv06P/30EyaTKddA+XE6nS7X4DEvBoOBoUOH4uLiAmTtYI6PjzcLqD/99FMGDx5MQkICP/30EwBLly6lUaNGuLq68uDBAwDCw8Pp27cvP/zwA3Xr1sXCwoJ169ZhZWXFzJkzATh27JhyyN/w4cM5ffo027dv5/jx4zk+ffr0UYLox82YMQM7Ozvl83hZkVedRqMhKCgIPz8/nJ2d2bx5s/IdOjg4cPr06RxjPDw88Pf3p169epQqVQq1Ws2wYcP+7akLIYQQQgghhBBCvDIkXBYvvYMHD5KUlERcXBxxcXF88803NG7cWLmOj49Hp9Mph7GlpaWxZ88edDodP/74IwAZGRkFqp87duxYypUrR9GiRalRowYajYZ33nmH6tWro1Kp+O2338z6BwQEoNVq6du3L5BVxuPq1au51l5WqVRKyY1Vq1axd+9evL29uXv3LuXKleP27dssWbKE1atXk5GRQXx8PPXq1eObb75h2rRpJCQkYGlpSe3atYGsww7v3btHaGgonTt3xs/Pj2+//ZYaNWpw/PhxnJ2dSU9Pz3Wdn332GYmJicrn+vXrBfzdeHV07NiR6OhofvjhB86dO0e1atWArNImtWrVynXM9OnTiYiIIDQ0lD///JNChQqZtffv35/9+/fnOja/NiGEEEIIIYQQQojXkdRcFi8to9GITqdDq9XmqFmcG51Oh0ajYdWqVahUKjIzM5k4cSIWFhakpKRgY2PzxGcEBgYyadIk6taty8GDB5UavT///DPTpk2jRYsWZv0HDBjAsGHDmD17tnKvePHibNiwgS5dutC6detc3/PLL79gZ2fHlStXaNq0KVeuXAGygs8vvviCP//8k9TUVO7cuYOnpycWFhbY29sTGRlJQkKC8hy9Xk/Hjh25f/8+VlZWWFtbExcXR7169bh48WKe5USsra2VMP51VqJECdq3b/9UY6pVq6YE0UIIIYQQQgghhBAibxIui5dWTEwMNWrUoFChQmbhsl6vR6fT4ezsbNb/4cOHrF27loCAAPr27UtUVBQzZszg9u3bXL9+nRIlShTovcWLF6d3795MnDiRwMBAUlNT+fjjj1m2bFmOvqVLl85xz9bWlg8//JCNGzfmGS4/Wg85IyODHTt2cOnSJUaMGEHfvn1ZtWoVJpOJDz74AEtLyzznevDgQTIyMrC2ti5QAP9EulRITfj7z/m36FKUX0ZFRTFgwAAuXbqEr68vs2bNMquznZvQ0FDGjh1LRkYGc+bMoWfPnjnaAwMD2bdvn9n9wMBApk6dio2NDUFBQTRv3vz5rUkIIYQQQgghhBDiFSHhsnhpVahQgYcPH+a4HxQUxOrVq3MtQTBt2jRKlixJ06ZNiYqKolWrVkDW4XcdO3Ys8LsnTZpEo0aNWLBgAXv27OHdd9/F29u7wOMnTpyY585gk8lEv379OH36NDExMej1ejZs2EDDhg2BrFrKb7zxBpmZmZw5cybf9xw8eJABAwZw//59atSoAUBmZibh4eF89913DB8+vMBzBuBqJFi+Wn8taK2ssLXS0rpFa9q0aUNISAgjR44kODiYAQMG5DkuKiqK3r17ExgYSIMGDejSpQt16tShSpUqAOzatYt+/frh6elpNm7Xrl2MGzeOkJAQXFxc6NOnD2FhYfkeoCiEEEIIIYQQQgjxOnq1UiQhnuDDDz/k3Xff5dy5c8q95ORk9uzZw9y5c3P0j4uLy7EDGsDGxobJkyfTpUsX3NzcWLVq1VPNI7+SEyqViubNm9OjRw9KlChBhw4dCAoKUtqvXr2KRqPBzs4OnU6X73uaN2/OhQsX6Nq1K7Vq1aJ///74+/vzzTffPH2wDByYOpcitkWeetyL5Gxrx4lDf5KYmMjcuXMpXLgwAQEBDB8+PN9wOSgoiGbNmuHr6wuAn58fq1atYtq0aVy6dAk/Pz+GDx/OsWPHzMYtWrSIfv360alTJwA6derExo0blecIIYQQQgghhBBC/FdIuCxeOWlpaXmWO3BxccHFxYWoqCgMBgMAX3zxBa1ataJUqVJAVribfdBd1apVOXToEJUrVwbgzp07HDhwgDVr1nD58mXWr1/Pnj17qFq1Ku+99x7NmjWjSpUqFCtWTKnHDFn1oY1Go9lcEhMTuXjxIsePH89Rw7d///6YTCYiIiLIzMwkIyODnTt3snr1anbu3MmCBQuIjo7Gw8MDLy8vunXrhq+vL1qtlvT0dGVtkFUOpEmTJgQEBBAYGEjLli1p2LAhycnJ2NraPtV3W8u9AkWLFn2qMS+DFZGReHl5UbhwYQBq1qzJ2bNn8x0TGRmJj4+Pcl2/fn2mTp0KZJUtCQsLY9OmTTnC5cjISHr16mU27uDBgxIuCyGEEEIIIYQQ4j9HwmXxykhNTaV169YcP36cQYMG5dtXp9Oh0+m4dOkSu3fvNquZW7ZsWQDefPNNXF1dqVSpEmlpaXh7e3P+/Hnatm3LkCFDaNeuHSqVivfee4+rV6+yYsUKZsyYwalTp/j6668ZNmyY8kyVSpUjXE5PT6dNmzbUqFEj1+Dxzp07tGrVivj4eCpWrEhcXBwWFhbodDrGjRtH4cKFcXJy4sSJE5w8eZLg4GCOHz+OXq8nPT2de/fu0bp1a4oVK0ahQoVwdHTk4sWL7N+/n9DQUP744w8+/fRTZYdtQZyMiX7pdy4729pR1qWY2b2kpCTc3d2Va5VKhVqtJj4+HgcHh1yf8/iYokWLcuvWLYA8xzxpnBBCCCGEEEIIIcR/iYTL4pVhY2PDuHHjKFKkCM2aNcu3b79+/ejXrx+QVVtXrVYrbS4uLjnCwMKFC7Nr1y7s7OzM+mZzc3Nj8uTJTJ48GaPRiMlkMmufOXNmjjEuLi7cv38/zzmWLFkyR3tmZiZOTk4cPnyYChUq5Druxo0baDQa6tevD0BCQgIGg4Hk5GRlTGZmJikpKfmGpLnxnjTmpa+5rLWy4vy8FWYBs0ajyVGKRKvVkpaWlud38PiY7P5P8qzjhBBCCCGEEEIIIV43L3eKJMRj3n333acek1tYnJtHy1zkx8LC4qnnUFDHjh3Dzc0tz2A5+/2lSpXi1KlTAGzZsoU6depQunRpAEJCQvDy8qJcuXJPPwE3D7B7iQ+m06WgizlBXHKiWbjs6OhIVFSUWdfk5GSsrKzyfJSjoyOxsbEF7v93xwkhhBBCCCGEEEK8bv65lEwIUSBTp06lXLlylCtXjo4dOxIdHa1cZ3+WLl1qNkalUqHX68nMzGTatGlcuHBBaZs7dy4XLlwgPT2dzMzMp5uM1gZs7F/ejzb3kh2enp4cPnxYuY6JiUGv1+f7A4PHx0RERCh1ufPzrOOEEEIIIYQQQgghXjcSLgvxgqWkpNC/f3+uXLlCXFwcqampXLlyRfk0bdoUnU6n9DeZTKjVaj755BNq1arFmTNnGDJkCLVq1VKuP/roI2rVqmVWa/pRer2epKQks8+rrEmTJiQlJbFixQoAAgICaNmyJWq1Wikb8riuXbsSEhLC6dOnSUlJYf78+bRp0+aJ7+rWrRsLFy7k5s2b3L17l2XLlhVonBBCCCGEEEIIIcTrRspiCPGCFaTMhqWlpfJrnU6HpaUl3377LQD169fH39+fBg0aAPDee+8xZ84cmjdvnufzZsyYwZQpU/7exF8iGo2GoKAgevbsyfjx47GwsGD//v1A1uF8ERER1KpVy2yMh4cH/v7+1KtXD61WS6VKlcwOacxLhw4d+Omnn6hUqRIALVq0oEuXLs97SUIIIYQQQgghhBAvPQmXhXjFpKam4uT0f3WRu3TpwuHDh5VSDY0bN6Z48eL5PuOzzz5jzJgxynVSUhJlypT5Zyb8L8kuKRIeHo6Xl5fyHT1++OKjpk+fTu/evbl58ybe3t45aif379+f/v37m91TqVSsWrWKkSNHkpqaire3NyqV6rmvRwghhBBCCCGEEOJlJ+GyEC+BWbNm8d133+XalpKSgpeXl3J9584dXF1d2bp1KyNHjsRkMmFnZ6cEnDqdjnPnzrFz506zHc+Psra2xtra+vkv5AUrUaIE7du3f6ox1apVo1q1ak/9Lk9Pz6ceI4QQQgghhBBCCPE6kZrLQrwEPv74Y+Li4nL99OjRw6zvpUuXKF26NB06dCAmJoZOnTrRvn17Tp48yd69e8nMzGTKlCl5Bsv50qVCasLL+7keA3uP0bR2PcaPH5/vruRsoaGhuLm54erqytq1a83aAgMDKV68OOXLl2fv3r3K/djYWFq1aoWNjQ2urq7Mnj274N+hEEIIIYQQQgghxH+E7FwW4hWzd+9eJk+erFzPmDEDb29vNBoNO3fuZMyYMbz11lvP9vCrkWD5kv61YDDC7j9Ru7rwy4+hfDVlCsHBwQwYMCDPIVFRUfTu3ZvAwEAaNGhAly5dqFOnDlWqVGHXrl2MGzeOkJAQXFxc6NOnD2FhYTg5OSmHJa5cuZJz587RtWtX6tatm28dayGEEEIIIYQQQoj/mpc0RRLiv8NgMPDVV18pB/Q9Li0tjfr16wMQGRnJ+fPn8fb2BrLqCZ8/f55atWoxbdo0ihcvjkql4uTJk5QuXRonJ6enqgd8YOpcitgW+dtr+ifs2/0rU/eFc2zPQaq4laNoQADDhw/PN1wOCgqiWbNm+Pr6AuDn58eqVauYNm0aixYtol+/fnTq1AmATp06sXHjRnx9fTl27Bjr16+nZMmSlCxZknr16nHp0iUJl4UQQgghhBBCCCEeIeGyEC9IRkYGlpaWpKen8+mnn/Lee+8RFRVFt27dUKvVSr/+/fuj0+kAuHnzJmPGjOHmzZv06dOH27dvo9fr+eijj7h//z4nT55k06ZNBAUFERUVRbVq1QgPD8fComAVcGq5V6Bo0aL/yHr/rq1319C4USOquJUDoGbNmpw9ezbfMZGRkfj4+CjX9evXZ+rUqUpbr169zNoOHjyIr68v1atXZ9GiRcyYMYPIyEiOHTtGYGDg81+UEEIIIYQQQgghxCtMwmUhXpA2bdrw5ptvMmvWLKytrRk3bhy3bt3i/fffN+sXHBys/Lpdu3a0a9cOgPXr11O2bFmaN2+OwWDAwcGBZs2a0axZMwAyMzNJTk4ucLAMcDIm+qXYuexsa0dZl2Jm95KSknB3d1euVSoVarWa+Ph4HBwccn3O42OKFi3KrVu3ntgWEBBAzZo1lUMWZ8+eTeXKlZ/P4oQQQgghhBBCCCFeExIuC/GCLF++nHfffZcff/yRHj168MMPP1C4cGFq1KiRo6+FhQXff/89b7/9do42o9HIgQMHmDFjhtn9YsWKKWFpQXlPGvNS1FzWWllxft4Ks4BZo9FgbW1t3k+rJS0tLc9w+fEx2f2f1Obv74+vry+TJ08mJiaG7t27U7lyZTp27Pjc1iiEEEIIIYQQQgjxqnvxKZIQ/1HlypXj8OHDaLVapk6dSufOnfn4448pX768WVmMpKQkSpcujZWVFUWKFCEhIeGJzz5+/DhdunR5+km5eYCd09OPe550KehiThCXnGgWLjs6OhIVFWXWNTk5GSsrqzwf5ejoSGxsbK7982pLSEhg+/btJCYmYmtri4ODAyNGjGD58uUSLgshhBBCCCGEEEI8QsJlIV6ABw8ecOzYMdq2bcvp06eZO3cu4eHhNGrUiJ9++okmTZqQkZGBSqXCYDBgZWVFeno65cuXJzMzk4yMDKytrXOUvMjMzESv16PRaHBxcXn6iWltwMb++SzyOfP09GTp0qXKdUxMDHq9HkdHx3zHHD58mEGDBgEQERFBqVKlzNpatGhh1mYymTCZTNy7dw9bW1sA7ty5g8Fg+KeWJoQQQgghhBBCCPFKKngxViHEc3P48GHef/992rVrh6urK8eOHWPt2rWo1Wo6d+5MlSpV8PT05MCBAxgMBjQaDQ0bNuTEiRP8/PPPODk54eTkhLOzM1ZWVtja2uLs7KzcNxgMhIeH5/l+vV5PUlKS2edl16RJE5KSklixYgWQVRe5ZcuWqNVqEhIScg1/u3btSkhICKdPnyYlJYX58+fTpk0bALp168bChQu5efMmd+/eZdmyZbRp0wYHBweqV6/OsGHDWLduHV999RXz58+XXctCCCGEEEIIIYQQj5FwWYgXoH379kRHR1OnTh3s7e2pWLEif/31FwcOHKB169YEBgZy8uRJWrRoQWZmplmZjO7du5OWlkZ8fDxxcXG0bt2aBQsWEBcXR2JiIjqdjrp16+b7/hkzZmBnZ6d8ypQp808v+W/TaDQEBQXh5+eHs7MzmzdvZubMmQA4ODhw+vTpHGM8PDzw9/enXr16lCpVCrVazbBhwwDo0KEDLVq0oFKlSri7u1O7dm2llMi6detIT09n8ODBzJw5k2HDhim7n4UQQgghhBBCCCFEFpXJZDK96EkI8V9lMBhQq9X06tULjUaDhYUFBw4coHLlypQsWZKMjAw+/PBD+vTpw7Vr14CsXceWlpZKSYx33nmHbt260b9/f+WZRqMRS0vLPN+r1+vR6/XKdVJSUlbAPH4COJb45xZcEKkJcO4g4bMWUqd8pRzNd+7cITw8HC8vL5ycClYf+uzZs9y8eRNvb+8cNZrDwsJITU3F29sblUr1PFYghBBCCCGEEEII8UpLSkrCzs6OxMREihYtmmc/CZeFeEEMBgOtWrVi69at3LlzRwmMhw8fTs+ePXnrrbcwGAzo9Xratm3L5cuXAXBzcyM2NpbChQsDWX/Yra2tsba2xmQykZaWRs+ePVm+fHmB55L9F8arEC4LIYQQQgghhBBCiH9WQcNlKYshxAvy+++/c/v2bWxsbKhQoQKdO3emdOnSFCpUCGdnZ/bs2cOKFSvQaDRmZTGuXr1KWloacXFxOcpizJ49mxs3bjxVsGxGl5oV7r7Ijy4lx7SioqLw9PTEwcGB8ePHU5CfiYWGhuLm5oarqytr1641awsMDKR48eKUL1+evXv3KvdjY2Np1aoVNjY2uLq6Mnv27Cd/Z0IIIYQQQgghhBD/UZoXPQEh/qvWr19Pnz59lOv4+HiuXbtGcnIy586d4+bNm2i1WqV0xpOYTCZ+/PFHfvrpJ7Zv3/5sJR6uRoLli/9rQWtlhbOtHZBVwqNDhw60adOGkJAQRo4cSXBwMAMGDMhzfFRUFL179yYwMJAGDRrQpUsX6tSpQ5UqVdi1axfjxo0jJCQEFxcX+vTpQ1hYGE5OTnzyySfUqlWLlStXcu7cObp27UrdunVp3rz5v7V0IYQQQgghhBBCiFfGi0+RhPgPSkxMZM2aNRw6dEi5V758eUaMGIGTkxMXL17kwYMHeHl5kZKSgkajwWQykZGRkaNmMGQFsKmpqSxcuJC5c+cSFxeHpaUl9vb2TzWvA1PnUsS2yN9d3t/mbGtHWZdiAOzYsYPExETmzp1L4cKFCQgIYPjw4fmGy0FBQTRr1gxfX18A/Pz8WLVqFdOmTWPRokX069ePTp06AdCpUyc2btyIr68vx44dY/369ZQsWZKSJUtSr149Ll26JOGyEEIIIYQQQgghRC4kXBb/GSaTicTERO7evcv169c5f/48165dIyAgALVajcFg4Msvv+STTz7B1tb2b70rIyMDlUqFRvN/f8SMRiOZmZlYWVlx8uRJihcvTvXq1ZX23377zewZRqOR999/n8mTJ9OpUyeio6OpUqUKWq3W7LA+o9HI/v37GTt2rHJv5cqV1K9fnwMHDjzVvGu5V8i3js6LEBkZiZeXl1JjumbNmpw9e/aJY3x8fJTr+vXrM3XqVKWtV69eZm0HDx7E19eX6tWrs2jRImbMmEFkZCTHjh0jMDDwH1iVEEIIIYQQQgghxKtPwmXxWvr1118ZMmQIBoMBo9GI0Wjk3r171KpVCwcHBxwcHHB0dMTBwYHLly9TqVIl1Go1x44d4+OPP2bRokXcuHEDNzc3ypQpozxXr9dTtmxZjh49qty7c+cOdnZ2vPPOO4wcOZJOnTqxcOFCFi1ahMlkIiYmhkqVKmE0Gqlfvz4//PAD3t7enDp1ymzOM2bMYNmyZVy6dAkACwsLPvzwQ3r27EmHDh2wtLTEYDAAsGHDBg4dOsTcuXMBSE1NpVChQlhY/F8ZdaPRSEZGhlkQ/SQnY6Jf6M7lR3csZ0tKSsLd3V25VqlUqNVq4uPjcXBwyPU5j48pWrQot27demJbQEAANWvW5LvvvgNg9uzZVK5c+fksTgghhBBCCCGEEOI1I+GyeC01b96c7du34+Ligr29PX/88Qe+vr4cOXJE6WM0GklPT6dIkf8LU+fPn8+ZM2cAsLa2xsXFhStXrijtR44c4ZNPPjF7V48ePfj888+xtrbG0tKShw8f4ufnh7+/P2fPnuWDDz7g+PHjOeZobW2d4/rxHdPNmjXDaDTmCIjT0tK4e/cuGRkZZGRkUL9+faytrbl9+zYWFhaULFkSo9GIr68vw4YNK/D35j1pzAutuay1suL8vBVmAbNGo8nxXWm1WtLS0vIMlx8fk93/SW3+/v74+voyefJkYmJi6N69O5UrV6Zjx47PbY1CCCGEEEIIIYQQrwsJl8VrSa1WM2vWLHbv3o2lpSXx8fGoVCoqVqyo9DEYDFSsWJF9+/YRHBzM559/roS4R44c4fPPP1f6vv322/Tv35/q1avnOCjP0tISjUaDhYUFw4cPx9LSkjVr1lCvXj2uX79O+fLlCzRnCwsLTp48aVZKw2AwMGPGDD799FMAxo8fz71797h27RpXrlyhV69eODs7K4F4hw4dGDx48LOHoW4eYOf0bGP/Ll0KupgTxCUnmoXLjo6OREVFmXVNTk7Otfb0o2NiY2Nz7Z9XW0JCAtu3bycxMRFbW1scHBwYMWIEy5cvl3BZCCGEEEIIIYQQIhcSLovXjsFgID09neXLlytBcIsWLRg1ahQdOnQw66vT6YiNjaVnz5706tULKysratWqRePGjc36GY1GnJ2dc32fhYWF8p5FixbRtm1bADp37kxsbCxJSUl069aNhw8fMmjQILp06ZLn3OvWrWu2y9lkMpGenq5cT5s2DaPRyObNm9m5cydBQUHo9XpWrVrFzJkzuXDhAhcuXGDChAkUKVLEbKd2gWhtwMb+6cb8wzw9PVm6dKlyHRMTg16vx9HRMd8xhw8fZtCgQQBERERQqlQps7YWLVqYtZlMJkwmE/fu3VN2kN+5c0cpRSKEEEIIIYQQQgghzEm4LF47x48fp2/fvhQqVAiVSsX9+/eVz8SJE836Go1G9Ho9y5cvp3HjxmzYsIEHDx7wzjvvkJKSovRTqVS5hsszZ87k0KFDDBgwgPj4eKKiorC2tuajjz7iyJEjnDx5khIlSgDg5+fHnTt3AEhPT1d2O+dHpVJhbW1Neno6VlZWBAYGcu3aNby8vICsQwAXLFiAj48PTZs2VXb4XrlyBU9Pzzyfq9fr0ev1ynVSUlK+83iRmjRpQlJSEitWrGDAgAEEBATQsmVL1Go1CQkJ2NraolarzcZ07dqVxo0b4+/vj7u7O/Pnz6dPnz4AdOvWjaFDhzJgwAA0Gg3Lli1j3rx5ODg4UL16dYYNG8bAgQOJiYlh/vz5fPvtty9g1UIIIYQQQgghhBAvPwmXxWunQYMGXLhwAciqTezl5cXQoUPNylzkJjY2Fn9/f7p3786JEyeoUKGCWVuxYsW4f/++2U7W8ePHM3ToUIoUKcLUqVNp164dDRo0wGg08vXXXwPg4eHBrFmzAJQwuU2bNhw8eNCsxIbJZMJoNJqVxci+7+DgQFxcHBqNBnt7e6XN2toaa2tr5bnr169n3bp1zJkzJ0fg+qgZM2YwZcqUfL+Pl4VGoyEoKIiePXsyfvx4LCws2L9/PwAODg5ERERQq1YtszEeHh74+/tTr149tFotlSpVUmpPd+jQgZ9++olKlSoBWbvas3eTr1u3Dj8/PwYPHoxarWbYsGHK7mchhBBCCCGEEEIIYU7CZfHaSk1NpWPHjvz111+sXbuWtWvXmrXHx8dTv359Nm7cSHJyMl26dOHmzZvExMTw/vvvs2vXLiAroL58+TKlS5fm/v376HQ65RkWFhZ8+umnuLq6cuLECRo0aMDnn3+Ot7e30ic5OTnHwXO//fZbjl3L3377LatXryYsLCxHXefsd6pUKkwmE3q9ntTUVG7cuIFKpVL6G41GtFrtE7+bzz77jDFjxijXSUlJlClT5onjXpSOHTsSHR1NeHg4Xl5eODll1YU2mUx5jpk+fTq9e/fm5s2beHt7KzWXVSoVq1atYuTIkaSmpuLt7a18f9WrV2ffvn3//IKEEEIIIYQQQgghXgMSLovXUlRUFO+//z52dnbY2toydOjQHH0OHz6shJOzZ8/m4cOH9O3bl0aNGvH2229jY2PDgQMH+O2336hUqRLdu3dnw4YN/PLLL8ozUlNT+fnnnzl+/Djh4eEkJSWxdOlSPvroI+XZGRkZFCtWzOzd+ZXD6NOnD1qtlv/973+4uroCKIFxZmYm8+bNw8rKCpPJxIULF3B3d1felZaWppThMBqNeb4je8fzq6REiRK0b9/+qcZUq1aNatWq5dqWX9kQIYQQQgghhBBCCPFk+Rd8FeIVFBERQf369enevTvLli1DrVZTokSJHJ+iRYsqIe/YsWP5/ffflUPixowZQ6lSpahSpQoLFy5k1KhRREREYGVlZRYUX7t2DT8/P2XX7+TJk+natSulS5dGp9ORmppKQkKCcphcZmbmE+e/aNEiHBwcqFq1KjNnzjQ70G/06NEkJCQwf/582rdvz4YNG/Dx8VGee/LkSaXcQ0ZGxnP4NoUQQgghhBBCCCGEyJ2Ey+K1U7t2bS5dusSXX36JSqUiMTGRr776Ksdnx44dyhg7OzsKFSqU41kbN24EssoyPGr+/PmkpaVRtWpVJk6cSEZGBrGxsRQpUoRvvvkGgM2bN7N161aaNWtGXFwcffv2pWXLlvnO3WQyUbRoUb7++mu2bdvG1q1buXbtWp7979+/T40aNXj33Xf54IMPCA0NpW7duhw6dIg1a9YU+DtT6FIhNeHFfHT/d4Dio6KiovD09MTBwYHx48fnWwojW2hoKG5ubri6uuYohxIYGEjx4sUpX748e/fuVe7HxsbSqlUrbGxscHV1Zfbs2U98jxBCCCGEEEIIIcR/mZTFEK+l7HISRqORkiVLcvz48Rx9goKCctTXNRgMSjmJo0ePMn36dHbu3InBYCAlJUUJkUePHk3fvn2xsrJi165dfPHFFzg5ObF582alhMX9+/f56quvOHjwIF988QVXr15l9erVec7ZYDCY7Wx+++23+eOPP3Lte/v2bXbs2MHBgwdZtmwZWq2WsWPHMmbMGDQaDZ988gkDBgygbdu2Oeo35+tqJFi+uL8WtFZWONvaKdd6vZ4OHTrQpk0bQkJCGDlyJMHBwQwYMCDPZ0RFRdG7d28CAwNp0KABXbp0oU6dOlSpUoVdu3Yxbtw4QkJCcHFxoU+fPoSFheHk5MQnn3xCrVq1WLlyJefOnaNr167UrVuX5s2b/xtLF0IIIYQQQgghhHjlSLgsXmsPHz7kxo0blCtXLkdbSkoKTZo0Mbun0+lIT09n165dzJgxg23btnHw4EE6dOiAyWTCxsYGlUpFkyZNcHBwYM2aNYwaNYp27dopJTiSk5N57733OH/+PNu3b6dy5cosWbKETz75hMaNG3P27Fmsra1JSUlhxowZTJ06FbVajU6nIykpqUDrioyMpFWrVixevJjo6Gg8PDzw9/dn3LhxAISFhdGiRQsqVqxIv379Cvx9HZg6lyK2RQrc/3lztrWjrMv/lR3ZsWMHiYmJzJ07l8KFCxMQEMDw4cPzDZeDgoJo1qwZvr6+APj5+bFq1SqmTZvGokWL6NevH506dQKgU6dObNy4EV9fX44dO8b69espWbIkJUuWpF69ely6dEnCZSGEEEIIIYQQQog8SLgsXmt169YtUJ3jbG5ubsyYMQMXFxdiYmJwdnZmwoQJGAwGateujZ+fH8HBwbi7uwPQq1cvypUrxzvvvMOGDRsoXbo03bp1A0Cj0dClSxfl2WFhYQwcOFA5SE+r1bJp0yaKFi3KJ598gre3N1OnTjULwlNTU2nevDnr1q1T7t24cYPAwEBq1qxJdHQ0NWvWxMfHhxUrVrB48WLu3r1LuXLlyMzM5K+//vo7X98LFxkZiZeXF4ULFwagZs2anD179oljfHx8lOv69eszdepUpa1Xr15mbQcPHsTX15fq1auzaNEiZsyYQWRkJMeOHSMwMPAfWJUQQgghhBBCCCHE60HCZSEeUahQIUaMGKGUudBoNKxatQoPDw/+97//UblyZbp160b37t2VMY0aNWLTpk18/fXX/Pzzz0RHR/Ppp59StWpVhg4dCoCVlRUajYZq1aop4zQaDd9//z0GgwEAa2trateuzZEjR5Q+ISEhZrWhAd566y1+/fVXrK2t0Wg0PHz4kKVLl6JSqdi+fTvLly8nNDT0mdbvPWnMCy+LcX7eCmX3clJSkhLkA6hUKtRqNfHx8Tg4OOT6jMfHFC1alFu3bj2xLSAggJo1a/Ldd98BMHv2bCpXrvx8FyiEEEIIIYQQQgjxGpFwWYhHqNVq5dcqlYqdO3cyePBgbGxsuHTpEj169MDCwoLp06czYcIEpTxDkyZNlBIbGo0mR53jzMxMZccywP/+9z++//57NJqsP4KjR4/G29tbaXd3d+f7779X5vEoS0tLNBoNFhYWvPvuu5hMJn7//XdKlCjB9evXKV++/LN/AW4eYOf07OP/Dl0KupgTxCUnKuGyRqMx+94ga8d3WlpanuHy42Oy+z+pzd/fH19fXyZPnkxMTAzdu3encuXKOQ5zFEIIIYQQQgghhBBZJFwW4jExMTHs378fgKZNm3LlyhWio6Pp0qULUVFRAJhMJnQ6HbGxsaxZswYrKyvq1q1L/fr1czzPYDBgMpnMQs2PP/6YTz/9FKPRSNmyZc2CZYD09HSKFy/OgwcPcjzPwsJCCZy3bNnCG2+8QUpKCq1atSI+Ph4LCwu6detGamoqX3zxBY0bNy744rU2YGNf8P7/MEdHR+U7z5acnIyVlVW+Y2JjY3Ptn1dbQkIC27dvJzExEVtbWxwcHBgxYgTLly+XcFkIIYQQQgghhBAiDxYvegJCvGwiIyNZvXo1kLWbtWHDhjRo0AC9Xo+Hhwc2NjY0bNiQxo0bk56ezvnz5/nhhx/45Zdfcn1edtmLR3dFW1tbY2lpyXfffUeFChWoVauW2RiVSoWzs3OOZ40cOZKrV6/SunVrYmJi6NChA5UrV2bjxo38/vvvHD9+nGPHjhEaGoparSYxMTHXOen1epKSksw+LyNPT08OHz6sXMfExKDX63F0dCzwmIiICEqVKpVvm8lkwmQyce/ePaXtzp07yu+dEEIIIYQQQgghhMhJwmUhHtO5c2eCgoIA+P777/n+++9Rq9X8/PPPbN26lbJlyzJ69GhOnDhBqVKlWLhwIW3btkWj0TB//nwqVarEjz/+yLRp06hYsaJS/9hoNJq958KFC0yZMoV27drx119/KUGmyWTi/v37Srj8aMD57bffcvv2bc6fP88HH3zA7t27OX/+PO+//77Sx9nZWdnta2GR+x/xGTNmYGdnp3zKlCnznL6956tJkyYkJSWxYsUKIKsucsuWLVGr1SQkJOQa/nbt2pWQkBBOnz5NSkoK8+fPp02bNgB069aNhQsXcvPmTe7evcuyZcto06YNDg4OVK9enWHDhrFu3Tq++uor5s+fL7uWhRBCCCGEEEIIIfIh4bIQ+Thy5AjdunWjT58+zJkzh9GjR5Oamsr06dPp3LkzV65cUfqqVCpGjhzJxYsX6d27N1988QWXLl2iV69eqFQqdDqd0vf27dt06tSJ5ORkTpw4Qf/+/ZXavxcuXMDOzk4po/HoOAsLC3r16sXq1av5448/ePjwIUOGDCEyMlLp8+DBA4oVK5bvuj777DMSExOVz/Xr15/H1/XcaTQagoKC8PPzw9nZmc2bNzNz5kwAHBwcOH36dI4xHh4e+Pv7U69ePUqVKoVarWbYsGEAdOjQgRYtWlCpUiXc3d2pXbs2Xbp0AWDdunWkp6czePBgZs6cybBhwxg0aNC/t1ghhBBCCCGEEEKIV4zUXBbiEenp6cyZM0fZubx27VpmzJhBcHAwmzdvJjIykk8++YTNmzezYMECXF1dC/RcOzs77t+/T+HChQH45JNPcHd3x83NjcGDB3PixAneeOMN1qxZwy+//ELJkiUZPHgw8+fPp1WrVspzbty4QXh4OBs2bGDOnDlcuXKFTZs28fXXXwNZBweq1WqcnPI/lM/a2jrHQXkvq44dOxIdHU14eDheXl7K2kwmU55jpk+fTu/evbl58ybe3t5KzWWVSsWqVasYOXIkqampeHt7K/Wrq1evzr59+/75BQkhhBBCCCGEEEK8JmTnshCPuHv3LrNnz1Z2JM+bNw93d3eOHTvGiBEjmDJlClevXmXcuHEUK1Ysx8FyixcvzvW5rq6u3L59WzlMbs6cOWzduhWtVotKpeLzzz/HxcUFNzc3li5dytChQzl37hyFChUyC4qvXLnC5MmTlZB6zJgxjBs3Til/cfnyZcqWLavUd87MzHyu38+LUqJECdq3b//E0PxR1apVo1WrVrke/ufp6UnTpk2VYFkIIYQQQgghhBBCPD0Jl4V4xPHjx6lcubLZvSpVqvDHH38watQoZs+ezbZt23BxceHUqVNKn/T0dFatWsX8+fPNylhkq1WrFhEREQwYMIDt27fj4uJidsBftvnz59O4cWM8PDyUe0lJSSxZsgSDwcBbb73FsGHDSElJITExkcqVK/Pxxx9TqFAhdu/eTVBQEO3bt+fmzZuMGzfO7DkFokuF1IQX89Gl5JhOVFQUnp6eODg4MH78+Hx3K2cLDQ3Fzc0NV1dX1q5da9YWGBhI8eLFKV++PHv37lXulytXDpVKZfYpV65cAb4wIYQQQgghhBBCiP8uKYshxP937949Tp48Sa1atYiOjkalUjF37lxWrlyJVqsF4OHDh0ydOhULCwtKly6tjN25cydqtZoDBw6g1WoxGAxmQWi3bt0YOXIkKSkpBAQEKPcNBoNy0N/mzZvZsmUL27dv59SpU8THx2MymYiKimLChAkMHjwYnU7Hxo0b+fzzz2nYsCFBQUGoVCo0Gg1nz55l3bp1hIeH8/7771OsWDGWLFnydF/C1UiwfHF/LWitrHC2tQNAr9fToUMH2rRpQ0hICCNHjiQ4OJgBAwbkOT4qKorevXsTGBhIgwYN6NKlC3Xq1KFKlSrs2rWLcePGERISgouLC3369CEsLAwnJydOnTplduDi7NmzuX379j++XiGEEEIIIYQQQohX2TOlSOnp6fzwww8MGjSIBw8eMG3aNDIzM/niiy8oUaLE856jEP+KsLAw+vbti7W1NXXq1OGDDz5gzJgxjBkzRumTkJDABx98wNGjR1m9erVy/6OPPqJ169a4uLgAWYfw6fV6pf3dd9/lwIEDnDp1ijfffFO5r9PpSE9PZ8WKFWzatImtW7dSqFAhKlSowL179yhSpAgZGRlMnDgRlUrFvHnzWLJkCVOmTKFv374A3Lx5k86dO5Oens6BAwdwdnZm27ZtDBo0CB8fH/74448CfwcHps6liG2RZ/4O/y5nWzvKumQdRrhjxw4SExOZO3cuhQsXJiAggOHDh+cbLgcFBdGsWTN8fX0B8PPzY9WqVUybNo1FixbRr18/OnXqBECnTp3YuHEjvr6+FC1aVHlGcnIyK1as4M8///wHVyqEEEIIIYQQQgjx6lOZCvLvzB/To0cPoqOjOXr0KH379lXqyKpUKnbt2vXcJynEv81gMChlK86cOYObmxtFimSFrmvXrsXd3R0vL6/n+k6TyaQcOKfT6Rg8ePAT5xYdHU2FChUICwujVq1aWFpaKv2MRiMXLlzgjTfeeOK7k5KSsLOz48DJEy8kXH40VM42ZcoUjh49yvbt24Gs78fJyYkHDx7k+ZxmzZrh4+PDxx9/DMDhw4eZOnUqO3bswN3dnZkzZ9K9e3cg6/fx4MGDLFq0yOwZs2fP5q+//mLZsmXPc4lCCCGEEEIIIYQQr4zsrCgxMdFsU97jnmnn8vbt24mIiMBkMrFz506uXLlCYmJigUIsIV4F2eFteno67du3p0mTJqxcuRKAnj175ug/f/58/P39c62jDFmB8NSpU5k4caLZ/djYWNq2bcu0adPw8fEBsgLRR0PivOZ2+fJlatSowZEjR/D09MzRz8LC4qn/THpPGvNCymJoraw4P2+FWcCclJSEu7u7cq1SqVCr1cTHx+Pg4JDrcx4fU7RoUW7duvXEtmxGo5GFCxeyYcOG57IuIYQQQgghhBBCiNfZM6VItra23Llzh6tXr1KhQgVsbW05ffo0dnZ2z3t+QrxQ8+fPx83NjRMnTvDHH3/w1ltv5dpPrVbj7e3N/v37c21v2rQpGk3OP24uLi5MnDiRQYMG0bRpUxYvXozBYKBs2bL5zstkMjFkyBAAWrRoYdZ2//59hg8fznfffVeAFT7GzQPsnJ5+3N+hS0EXc4K45ESzcFmj0WBtbW3WVavVkpaWlme4/PiY7P5Pasu2c+dOXFxcqFOnzt9elhBCCCGEEEIIIcTr7pnC5XHjxtG0aVNUKhXff/89p06dokuXLgwdOvR5z0+IF+bAgQN8/fXXhIWFcefOHbp27crevXupWLFijr557Vh+1OPhcmJiIpaWlnTu3JmGDRvy/fffY2tri16vp3Dhwvk+a8KECdy7d4/ixYuzdetWpY7zl19+yW+//cbcuXOfYqWP0NqAjf2zjX3OHB0diYqKMruXnJyMlZVVvmOyy/Q83j+/tmxr1qxRymYIIYQQQgghhBBCiPxZPMug0aNHExUVxYULFxgwYAAuLi6sWrWKyZMnP+fpCfFihIeH06dPH0JDQ7GxscHT05PJkyfTrFkzzp8/n6O/SqV64jMfD6C/+uorKleuzI8//kjx4sWZNGkSKpWK1NTUfGvZLF68mM2bN7N3715WrVpFx44dCQoKomfPnhw8eJDt27fnG8C+Kjw9PTl8+LByHRMTg16vx9HRscBjIiIiKFWq1BPbAPR6PVu2bKFLly7PcxlCCCGEEEIIIYQQr61nCpcBqlSpQrly5QAoWbIkrVq1el5zEuKF+uWXX2jXrh1LlixBo9Hw5ptvcv36dQYOHMioUaNo0KABISEhZmMKEi4/3icgIIDp06czcuRIPv/8c+V+QkICTk55l6YYOHAgv//+O87OzlSvXp1GjRoxYcIENm3aRN++fTEYDE+ci16vJykpyezzsmnSpAlJSUmsWLECyPq+WrZsiVqtJiEhIdd1du3alZCQEE6fPk1KSgrz58+nTZs2AHTr1o2FCxdy8+ZN7t69y7Jly5Q2gEOHDmFvb0/58uX/nQUKIYQQQgghhBBCvOKeKVzOyMggICCABg0aUKpUKc6cOUP9+vWJjo5+3vMT4l+TkJDAgAEDGDRoEBs3bsTHxwcvLy86dOhAx44dMRgMjB07loULFzJo0CAaN25MfHw8kBUcHzp0CGdn51w/hw4dMguXMzIyyMjIoF+/fkRERDBq1CilLTY2lmLF/q/2sMFgIDU1FYArV67w66+/EhQURLt27WjevDmNGzfm66+/ZseOHezbt49y5cpRpUoV2rdvz5gxYzCZTDnWOmPGDOzs7JRPmTJl/qFv9dlpNBqCgoLw8/PD2dmZzZs3M3PmTAAcHBw4ffp0jjEeHh74+/tTr149SpUqhVqtZtiwYQB06NCBFi1aUKlSJdzd3aldu7bZLuV9+/bRqFGjf2dxQgghhBBCCCGEEK8BlSm35OkJBg8eTFhYGB999BHjx48nMjKSefPmERUVxZ49e/6JeQrxj9PpdEyYMIGxY8fi4uKilJZIS0vj0KFDZrvzL126xNatWxk9ejQAQUFBrF69Ot8D/Tp37qyEyIsXL+ajjz56qvmZTCZ27drFN998Q/PmzWnZsqVy8JxWq+XMmTNUqFCBjIwMjh8/zqlTp3Bzc6Nt27Y5nqXX69Hr9cp1UlJSVsA8fgI4lniqef1tqQlw7iDhsxZSp3ylHM137twhPDwcLy+vfHd0P+rs2bPcvHkTb2/vHCVCwsLCSE1Nxdvbu0A7zoUQQgghhBBCCCH+a5KSkrCzsyMxMTHf8q3PFC47ODhw/PhxKlSogIODA5GRkVhaWlK5cmWSk5P/1sSFeNEyMzOxtLTM9ZA+k8mE0Whk2bJlDBw4ULm/dOlSfvzxx3zD5U6dOilh9MOHD3n48CHW1tZm7/n+++/ZsWMHmzZtUu4ZDAZ0Op0SrI4ePZrAwEC0Wi0WFln/+CAxMRFbW1ssLCwwmUzodDo6derE+vXrC7Tm7L8wXsZwWQghhBBCCCGEEEL8uwoaLj9TWYwyZcpw8OBB5VqlUnHmzBnc3d2f5XFCvFQ0Gg0Gg4HMzMwcn/bt2+Pt7U2vXr3MxhTkZzSP9ilUqBCOjo7Y2Nig1WrRarVER0cTEBBAQEAAkyZNIiIiAq1Wi42NjdmO3W+++Yb09HROnjzJlStXSEhIwMbGhlOnTnH27Fnu3buHXq8vcLBsRpeaFfb+mx9dSp7TiYqKwtPTEwcHB8aPH1+g7zk0NBQ3NzdcXV1Zu3atWVtgYCDFixenfPny7N27V7lfrlw5VCqV2Se7prwQQgghhBBCCCGEyJ3mWQbNmjWLzp07s2TJEtLS0hgzZgy///47K1eufN7zE+KFyN4R/KilS5dy8uRJTpw4gVarNWszGo1PfGZ+B+1t2bKFYcOGMX/+fGrXrs2+ffto1aoV/fv3Z9asWRQuXNis/59//kn37t35+OOPGTlypHJ/4cKFrF27ltmzZ5vVEy6wq5Fg+Ux/LfwtWisrnG3tzO7p9Xo6dOhAmzZtCAkJYeTIkQQHBzNgwIA8nxMVFUXv3r0JDAykQYMGdOnShTp16lClShV27drFuHHjCAkJwcXFhT59+hAWFoaTkxOnTp0y+z2cPXs2t2/f/sfWK4QQQgghhBBCCPE6eKayGJBVc3b9+vXcuHGD0qVL06NHD8qXL/+85yfES+HChQt4enqybds23n777RztgYGBjBo1Kqu0RC4SExOZOnUqn332mdn9P//8k+nTp3PhwgVCQ0Px8PBQ2i5dukS/fv2IjY1l5cqVeHl5kZqayhdffMHWrVv5/vvvadiwIdeuXaNmzZpcvHgRNzc3/vjjD4YMGUKFChUICQnBxsbmievL/qcOB06eoIhtkaf8dv4+Z1s7yroUM7u3adMmBg4cyI0bNyhcuDCRkZEMHz6cP/74I8/njBo1ir/++oudO3cCMG/ePGJjY5k2bRqdO3emRIkSLF68GMgqL1K9enV8fX3NnpGcnEyVKlX4888/ZfeyEEIIIYQQQggh/pP+0bIYABUrVmTChAksXLiQCRMmSLAsXlt6vZ6ePXsybNiwXINlyNqV3LhxY+Li4nL9NG7cmMzMTKW/0WikV69edO3aFW9vb06dOmUWLEPWn7EDBw7w3nvvcfPmTQAKFy5MzZo1iYyMpEWLFvzyyy9Ur16d1q1bU6pUKQDeeustIiIi6NmzZ4GC5ZdVZGQkXl5eyq7tmjVrcvbs2SeOad68uXJdv359wsPDn9j2qMWLF+Pj4yPBshBCCCGEEEIIIcQTPNO/f9+5cycNGjTAwcHhec9HiJdOeno6Xl5eTJo0Kc8+I0eONCtP8bjHD/qzsLDg+++/5+7du1SqVIkPPviAQoUKKe+zsrICoEiRIkRERFC1alUgq775o2UhOnTogLW1NWPHjkWj+b8/ztbW1jnqQheE96QxL6wsxvl5K8x2LyclJZnVcVepVKjVauLj4/P8u+fxMUWLFuXWrVtPbMtmNBpZuHAhGzZseC7rEkIIIYQQQgghhHidPVOKNHToUJYuXUqrVq2e93yEeOnY2toSGBj4jzw3LS0NQPnnBWlpadSsWZPNmzdTvXp1tFotlpaWypixY8fy888/m+1ILlq0KL6+vko4bTQaMRqN/PXXX08/KTcPsHN6cr/nSZeCLuYEccmJZuGyRqPB2trarKtWqyUtLS3PcPnxMdn9n9SWbefOnbi4uFCnTp2/vSwhhBBCCCGEEEKI190zhcsjR47k22+/pVmzZma7JYUQBWMymUhLSyO75LmFhQVpaWkULlyYd955h/79+3P48OEc4+bMmcOcOXPYv38/K1as4IcfflDafvvtN4KDg/nhhx9yPZCwQLQ2YGP/bGOfM0dHR6KioszuJScnK7u68xoTGxuba//82rKtWbOG7t27P4/pCyGEEEIIIYQQQrz2nimBcnJyIj4+nrp167Jo0SJWrlypfIQQT3bt2jWcnJyoUqUKAK6urjg5OWEwGJg6dSoDBw5ErVbnOb5hw4YcOHCAbdu2Kfe++eYb3nzzzWcPll8ynp6eZgF7TEwMer0eR0fHAo+JiIhQalHn1wZZtbW3bNlCly5dnucyhBBCCCGEEEIIIV5bKlP21smn0KxZs9wfplKxd+/evz0pIf4rEhIScHBwICMjQ/lXADExMUptYHt7e44fP07FihWJjIzknXfeoUiRIqjVahITE7Gzs1OedfXqVUqXLo1arUan0+Hk5MTRo0dzfa9er0ev1yvXSUlJlClTBsZPAMcS/+CKc5GaAOcOEj5rIXXKV1JuZ2Zm4urqysyZMxkwYACDBw/mzp07bN26lYSEBGxtbXME8JGRkTRu3JjDhw/j7u7O22+/TZ8+fRg7dixbtmxh6NChhIWFodFoqFu3LvPmzaNr164A7N27l/79+3Pt2rV/c/VCCCGEEEIIIYQQL52kpCTs7OxITExUyrnm5plqWuzbt++ZJyaEyCk+Pp6//vqLQoUK0bJlSw4dOkT16tXN+nh4eHD9+vXn8r4ZM2YwZcqU5/Ksf4pGoyEoKIiePXsyfvx4LCwslIMRHRwciIiIoFatWmZjPDw88Pf3p169emi1WipVqsSwYcOArMMPf/rpJypVygqwW7RoYbZLed++fTRq1OhfWZsQQgghhBBCCCHE6+CZdi4LIf6e+Ph4jh49yr59+5g1axaVK1dm8ODBjBs3jqlTp5KZmcnUqVPNdi5n++WXX3jvvfdwdXXN8VydTgfAjRs38n3/q7BzOdudO3cIDw/Hy8sLJ6eCHTZ49uxZbt68ibe3d466ymFhYaSmpuLt7Y1KpXoeKxBCCCGEEEIIIYR4rfyjO5ctLCzyDGUMBsOzPFKI/5QjR44wbtw4unXrBsCZM2eUshgTJ05EpVKRmZmJyWRi7969bNmyBR8fH6pWrYqVlRXly5fPcdgdwJ49exg0aNAT329tbY21tfXzXdQ/pESJErRv3/6pxlSrVo1q1arl2ubp6fk8piWEEEIIIYQQQgjxn/dMJ3/FxMRw+fJlLl++TFRUFMHBwVSvXp01a9Y87/kJ8Vpq27YtZ86cYfTo0cq9HTt28OGHH9K6dWsqVqxIuXLlSE5OZu/evZhMJmxtbYGs2uaXLl2iRo0aOT6DBw/+e7txdalZO4n/zY8uRXl9VFQUnp6eODg4MH78eAryDytCQ0Nxc3PD1dWVtWvXmrUFBgZSvHhxypcvn2s9+Dt37uDk5ERYWFjBvh8hhBBCCCGEEEIIoXimnctubm5m11WrVqVt27Z06NCB999//7lMTIjXWW4BsL29PdWrV6dXr168+eabODo6YmNjw9SpU6lcubJZ34oVK+a5c9nX1/fZJ3Y1Eiyf6a+Fv0VrZYWtlZbWLVrTpk0bQkJCGDlyJMHBwQwYMCDPcVFRUfTu3ZvAwEAaNGhAly5dqFOnDlWqVGHXrl2MGzeOkJAQXFxc6NOnD2FhYWalNUaOHEnXrl1lN7MQQgghhBBCCCHEM3huKVKhQoW4c+fO83qcEK+9Gzdu8Ouvv6LRaFCr1TRs2JCGDRua9TEajWRmZprdy8jIyPe5f6c0zYGpcyliW+SZxz8rZ1s7Thz6k8TERObOnUvhwoUJCAhg+PDh+YbLQUFBNGvWTAnU/fz8WLVqFdOmTWPRokX069ePTp06AdCpUyc2btyo9P3ll1/Ys2cPFy5c+OcXKIQQQgghhBBCCPEaeqZwuVmzZmY7L41GI2fPnqV169bPbWJCvO7++OMPFi1axPLly/MsZZGenp4jXM7MzFTKYjwuNTWV9PT0Z55TLfcK+RZp/yetiIzEy8uLwoULA1CzZk3Onj2b75jIyEh8fHyU6/r16zN16lSlrVevXmZtBw8exNfXl4cPHzJ8+HDatm3Ltm3baNy4MZUq5TxMUAghhBBCCCGEEELk7ZnC5f79+5tdq1QqSpUqRfPmzZ/HnMQLlJGRQUZGBtbW1qjV6lz7GAwG9Ho9VlZWyiF0z8JoNGIwGLC0tHxi3+yANb/3ZWRkkJ6ejo2NzTPP6d/Uo0cPevTokW+f3HYht23bltjYWKUG8/N0Mib6X9u57GxrR1mXYsp1UlIS7u7uyrVKpUKtVhMfH4+Dg0Ouz3h8TNGiRbl169YT2+bNm8eNGzcoWrQop06dYvz48cyfP5+ePXs+1zUKIYQQQgghhBBCvM6eKRns16/f856H+IeYTCYsLCyIioqievXqT+y/bNkyPvroIyAr3DOZTErIbDQazZ67Y8cO2rZtS3p6OtbW1jg4OGBhkf8ZkUlJScyePRt/f38OHjxIs2bNsLCwMNu5azAYzIJtk8mE0Whk0aJFDB06NM9nnzt3jiZNmnD9+nWaN29OUFAQHh4eT1zz3/H777/TokULXF1d8+2XmZlJSkoKCQkJZvd79uzJsGHDePvtt5V7M2bMYP/+/ezatSvXZ61bt47Q0FA2bdrE7du3KV++fI7f2/DwcAwGwxN/Px7nPWnMv1ZzWWtlxfl5K5SAWaPRYG1tbd5HqyUtLS3PcPnxMdn9n9S2ZMkSxowZw6xZswCoW7cuY8eOlXBZCCGEEEIIIYQQ4ik8U4o0a9YsRo8ebbbjdO/evUyZMoUDBw48t8mJv0+lUmFtbY1WqwVg37593Lt3j6ioKE6dOsWpU6eIi4ujYcOGrFy5ksGDBzNo0CAsLS0JDg4mKCiIP/74A4AvvviCGzduEBwcjNFoVAJhKysrrK2tOXHiBOXKlQPg4cOHFCpUSJlHeno6VlZWvPPOOxQpkrUztkmTJsoO6GxGoxFra2sSExOV8giQFTibTCbl17ntqtZoNNja2mJra8ucOXNYtGgRCxcuzBGwli1bFj8/Pz7++GPlXrly5bh69SoAJUqUoG/fvgQEBKDRaPJts7S0pHLlysrherGxsXTq1IkNGzZQsmRJ5flXrlyhfv36OeYcHh5OSkqK2T1ra+scIeujChUqhKWlJWfPnjV7x6MsLS2fOlgGwM0D7Jye3O/v0qWgizlBXHKiEi47OjrmOKQwOTnZ7P+Pxzk6OhIbG5tr//zabty4wTvvvKO01alTh9u3b5OWlmb2/50QQgghhBBCCCGEyNszhcufffYZQ4cONQuXq1WrxpEjR57bxMTfYzKZ0Ov1SnkLlUqFXq9n3bp1XLx4EZVKxdmzZ7G2tsbT0xOdTsf9+/cpUaJEnuUwHvV4cKnRaLh48SJHjhyhR48efPvtt4SHhxMaGgrAl19+qYzJfr6FhUWO4PDevXvY2NjkCPgendOoUaMICQnJUf7CYDBw69YtJeDOzMwkJCSEmzdvKn3PnTvH9evX2b17t1m4DLB69Wp8fHy4ePEiH3zwAaVKlcLf3z/ftsfnP3r0aI4fP64czKdSqdiyZQu2tra5hr3ZAfWjVCpVnsHwkiVLSEpK4ubNm7Rt25bjx49TokQJvvrqK7N+j9YhfipaG7Cxf7axf5OnpydLly5VrmNiYtDr9Tg6OuY75vDhwwwaNAiAiIgISpUqZdbWokWLHG2lS5fm4cOHynOuXr2Kg4ODBMtCCCGEEEIIIYQQT+GpwuWDBw8CWcHloUOHlMDOZDKxe/du3njjjec/Q/FMrl69SuXKlSlcuDBpaWnUqVMHg8HArl27aNSoEZBVO7t06dJMmzbtubzT2toaf39/GjZsyP79+2nfvj316tVj37597N+/n3HjxhEZGZlj3IgRI9i6dSvwf+UjsgNiyNqBeuLECeV6wYIFLFiwIMdzUlNTcXBw4MqVK3nO8ddff8Xb25tDhw7l2F1tY2ODo6MjDRo0YMiQIWzfvl0Jl/NqezQEXrBgAWvXrmXJkiUMGjSIMWPGkJCQwJtvvpnnnFQqFX369FF2lgPodDoyMjJwc3MjMzMTg8HAnTt3AAgICKBv376ULVsWlUrF0aNHadOmjRLiZ/P19cVoNOYZUuv1evR6vXKdlJSU53f2b2nSpAlJSUmsWLGCAQMGEBAQQMuWLVGr1SQkJGBra5vjBx9du3alcePG+Pv74+7uzvz58+nTpw8A3bp1Y+jQoQwYMACNRsOyZcuYN28ekFWOZOLEiZQuXRqDwcCECROkJIYQQgghhBBCCCHEU3qqcDm71rJKpWLo0KFKcGVhYUHFihVZuXLl85+heCblypUjPT0dgCJFinDy5EmzwPafULZsWSZOnMjw4cM5efIkmzdv5vDhw0yYMIELFy7wzjvvsGLFihzjEhMT6dOnT64h9/79++ndu3eO+x988IHyww6ALl26MHfuXKysrHjw4AGOjo4EBATQvn17s7rLu3fvpnPnzty8eZODBw/Spk2bXNei0WiU768gbQ8ePGDlypUcOXKE999/n3379hEdHc1vv/2W+5f1/6WmprJu3Tq8vb3z7Qdw9+5dEhMTqV27NhcvXiQoKIg+ffqY1at+VMOGDTl69GiubTNmzGDKlClPfOe/SaPREBQURM+ePRk/fjwWFhbs378fAAcHByIiIqhVq5bZGA8PD/z9/alXrx5arZZKlSoxbNgwADp06MBPP/1EpUqVAGjRogVdunQBYPLkyej1elq2bElKSgrt2rVT6i8LIYQQQgghhBBCiIJ5qqKsMTExxMTEYDKZOH36tHIdHR3Nrl27/vHD08Tf89dff5kdyve4FStWULhwYezt7XF2dmbEiBEcPXoUZ2dnnJ2dmTt3LiEhITg7O2NnZ6fUTn7URx99xJUrV2jbti1arZavvvqKJUuW8O677+ZZR/jR3bVnzpyhbNmy3Lt3T7mXW3iamJjI4sWLuXLlCpMnT1Z23laoUIHLly+TmJjI9OnTzdabkZHBgQMHaNiwIQ0bNmT37t25zufu3bv8+OOPuQa+ebU5Ojpy7Ngx0tPTcXR0ZNeuXdjb2xMREaHUis5NUlJSvvWVHxUVFUXHjh2V76tq1arEx8dz/Phx7O3tCQ0NpXPnzvj5+XH8+HEuXryY57M+++wzEhMTlc/169cLNId/WseOHYmOjuaHH37g3LlzVKtWDcj61xGPB8vZpk+fTkREBKGhofz555/KbnSVSsWqVas4cOAA27dvZ8uWLcr/S5aWlnz99dfcvn2b5ORk1q1bl6PMihBCCCGEEEIIIYTI3zPVXG7Tpk2OOrHi5XTlyhUMBgPt27fHYDAQERFhVgriUV27dqV169ZKcPzll19y4cIF1q5dC5gf6JeamkpqamqOZ5hMJnQ6HWFhYaSnp+Pi4oK9vX2BD5dLSEjAYDBQrFixfPtlZmaaXRsMBiBrJ2tERARbt27l3XffpXbt2kqfP//8k4yMDGrXrk2jRo1YuHCh2TN69+6NWq0mNTWVLl26MH78+AK1QVbJmEGDBqHRaOjVqxedO3dm37599OjRg7S0NEJCQnKswWg0kpycTNu2bdFocv5RrFGjhrJzF7J23rZo0YJNmzYBWYck3rz5/9i777gsq//x46+bvREQB4qgpeRIHICoKa5CRdREzT1x5MCJTc2JOdI0UT+iaWmJimlm7j0zREARlRxg4sLBhpt1//7gy/XxlilqfX71fj4e1yOu65z3uc65Mf54c3ifeFxcXIiJiaFr1648fvwYAwMDVqxYUeT3p0Bphwb+napUqYKXl9cLxdSrV09JRD/P1dX1VUxLCCGEEEIIIYQQQjynXMnlvXv3Fvk8Kyur0AFn4u8RFhZGv379SEtLIzs7m6+//pp33323xBgLCwssLCyU+4MHDxZbh9bU1LTInZ5BQUE0aNCAR48e8c033/DkyROcnZ358ccfmTx5cpFjPbu7OCYmplAysKjd1mq1msGDB2NsbExqaqpS3qJ169asX7+emJgYzp8/rxVz4MABsrKyqFSpEjk5OaSlpXH//n2qVKkCwNKlS/H09KRSpUqFEvAltQE0a9aMoKAg2rRpw5o1a2jdujVubm5ERkZy7do1qlatWijm+vXr6OrqkpCQUOiXNTt37iQgIKDIz6uAgYGBsmPbwMCg2PIYLyQzDdISX36cUt+TWuhRVFQUQ4cO5fr16/j6+rJw4cJS1xQSEsKUKVPIzs7mq6++0vr3GhgYyOzZszE1NWXt2rW0a9dOK/b+/fvUr1+fffv2SQJaCCGEEEIIIYQQohzKlVy+f/8+c+fO5dq1a8qOUY1Gw5UrV5SDx8Tfq169eixevBgvLy8sLCyUurNldfbsWX7//fcid9wW5+HDh8yaNYvDhw+TnZ3NxYsXmTNnDhcvXmT+/Pl8+eWXRcY9e7Dcli1b8PLyIjk5GSMjI8zMzKhTp06hmEOHDilfazQaoqKiiIuLo3PnzowYMYJ58+bh4OCgFXPw4EGmTJnC2LFjAXBzc+PgwYMMHDgQgEqVKhWKKVBSG+TvBG7Tpg2HDh1Co9Fw/vx5Dhw4gLW1Nc2bNy/yQL/Dhw/TrFmzIv8KQKPRlGm399dff82iRYswMDCgRo0aADx9+pT4+HiOHDmCm5tbqWNoiYsE/XL9WHhhRgYGVDS3BPL/DXh7e+Pp6UlwcDB+fn5s2LCBoUOHFhsfFRVF//79CQwMpFmzZvTo0YMmTZrg5OTE/v37mTp1KsHBwdja2jJgwABCQ0OxsbFR4v38/PDx8ZHEshBCCCGEEEIIIUQ5lSuLNHDgQGxtbTExMSEnJ4cuXbowZ84c5SAt8fczNjbG29u7XLGJiYkMGTKEYcOGKQlLyN9BXFL94F27djFs2DDq16+PRqNh4cKFLFq0iBo1arBw4UKMjIx4//33C8Vt2rQJlUrFokWLuHz5Mtu2bWPu3Lls376d+fPna5WGgPxfbkRERBAWFqYkwe3s7Fi5ciUrVqzAxsaG27dvA3D06FGlFnhYWBhLly5VDjZs164dBw4cUJLL5fF8eY68vDx27tzJxIkT6dy5M7169aJixYpK27PWrVvHoEGDihxXo9GUWB+7wEcffUSfPn3o1q0bU6dOpUqVKkydOpXVq1e/eGIZOD57CWbmhWtpvw4VzS2pYZtf/mTv3r0kJSWxZMkSTExMCAgIYOzYsSUml9euXUvbtm3x9fUFYNy4cWzcuJG5c+eyatUqBg8eTLdu3QDo1q0bO3bsUPr++uuvHDp0iJiYmNe8SiGEEEIIIYQQQoh/rnIll3/77TeuX7/OH3/8waeffsqHH36Io6Mjc+bMYcaMGa96juIlFZcQLip5ee7cOYYMGYKZmRlfffVVof4FO9Wfl5ubi6+vr5K4ValU/Pjjj0p7VlYW165d4+bNm+jq6irP09LSOHjwIMuWLePPP//k8OHDmJubs2DBAlq2bMmkSZNYs2YNQUFBytjffvst33//Pd7e3vj5+dGiRQvi4+MZPHgwb7zxBtHR0Tg7O+Ph4cHixYvp06cPjo6OmJiYaCVc27dvz4wZM0pMmJcmOztb6/69997jvffeIyIigq+++kprp+yziejvv/+eq1evFptczsvLK5S4LpCVlaX1fVCpVHzwwQcMGTKEvLw8Pv74YypVqoRarX7husqNar6hVRrlrxIZGYm7uzsmJiYANGzYkOjo6FJjOnXqpNy7ubkxe/Zspa1fv35abSdOnMDX15eMjAzGjh1Lx44d2b17Ny1btnzhnf1CCCGEEEIIIYQQopzJ5WrVqnHgwAF69+5NdHQ0GRkZNGjQgEuXLr3q+YmXcPDgQTZt2oRarcbKykp5fu3aNX744Qf279/Pxx9/rBUTGhqKvb09W7duxdzcXKstOzubzMzMQu/Jysoq8vmz1Go1nTp1wsbGhsWLFzNw4EAuXryIi4sL9vb2pKSksG7dOq0SGF27dqVDhw7Url2bjh07cvXqVQA+/PBDPvvsMy5fvoyuri4RERG0a9eOmTNnMn78eFQqFVu3bqVLly5YWVkxcuRILC0t6dWrl9acRowYwYgRI4D8gw+3bdtGREQEjRo1Ijc3l5ycHPT19bl48SKWlpZkZGRgaGhIdnY2KpUKfX19cnJyuHz5MkZGRhgZGSlj5+XlkZqayvbt2zEwMCiUyI+NjWXmzJlUqFBB6/kXX3zB/Pnz0dPTQ61WY2ZmRqVKlbh586bWZ5mVlcXBgweZNGkSb731Ft7e3ty7dw+VSsWvv/7K119/TXh4ODt27MDe3r7E782zIm7d+Et2Lj+7axkgOTmZmjVrKvcqlQpdXV2ePn2q9W/3Wc/HWFhYcPfu3VLbli1bxp07d7CwsODixYv4+/uzfPnyYuuLCyGEEEIIIYQQQoiilSu5vGDBAvr27UvHjh3x9vbGxcUFjUbDO++886rnJ15C1apVsbS0ZN++fVhaWirP7e3tuXDhAn5+fowcOVIrZty4cYwbN67I8Z7fyVzAwMCg1N2/W7ZswdrampSUFP78808aNGgAgKOjIwYGBvz555+MGzeO8ePHs2LFCrp06QLAkydPePLkCYcOHSIrKws9PT0sLS3R1dVVdkA3atSIW7duaa2xVatW3L59G11dXczMypYsdXBwoGvXrmzdupXc3Fz8/PzQ09NT1tamTRs0Gg25ublMmjSJ/v374+bmxm+//cagQYMYNGgQ/v7+ytwuXLjA9u3bmTdvHpCfhC9gZmbGxx9/zNy5c9FoNBgZGfHgwQMMDAzo168fGzZsAODYsWOFys0MHDhQKeURFRWl1ZaZmcnixYtZtGgRQUFBZVr3szxmTP5Lai4bGRhwbdl6JcGsp6dXaJe1kZER6enpxSaXn48p6F9a25o1a5g8eTILFy4EoGnTpkyZMkWSy0IIIYQQQgghhBAvqFxZpG7dunH37l3MzMxYs2YNP/74IykpKQwePPhVz0+8hAYNGrB8+fJCz01MTNi9e/dfOpdJkyYxadIk1q5dy6ZNmwrVUXZ0dGTt2rV06NBB6/mKFSvo378/devWpXHjxsyfP5+OHTtq9QkPD6dx48aF3vlssrks3NzcWL16NcePH+ejjz6iV69eSjI5NDSU7t27o9FoyMnJUepZGxoa0qxZM44cOYK+vj5Dhgzhp59+wsTEhOzsbHJzc/nPf/5DVlYWGRkZPH36FDMzM/T19ZUk8v3793FxcQHyE/XPK8vBfgDp6en06dOH8+fPv9C6tTg4g6VN6f1eRmYqmbcu8CglSUkuW1tbF0qUp6SkFPl5FLC2tiYhIaHI/iW13blzR/nlBUCTJk24d+8e6enpSlkOIYQQQgghhBBCCFG6cm9RLPhz/qysLGUXZVmTYEKURVJSEmvWrCEgIAAAfX19ZTeqRqNhxowZ/PDDD6Snp3Pv3r1X8s7OnTvTuXNnADw8PNDV1SUnJ4fp06fToUMHpRZyQQmMjIwMrl+/zttvvw2gVWd68eLFREVFKbuQn6Wvr691r6eX/7+iSqUiIiKCmTNnAvnlM8pq7Nix1K1bl8jIyDLHFGJkCqYVyh9fTq6urlo7rW/duoVarcba2rrEmLNnzzJ8+HAg/5cM1apV02pr3759obbq1auTkZGhjBMXF4eVlZUkloUQQgghhBBCCCFeULmywSkpKYwcOZLKlStjYmJCVFQU1atXJyws7FXPT/wDhYWF4eLionUVlRxeuHAhSUlJWs/WrVuHq6ursoN4wYIFWgcEllenTp2wt7enYcOGQH495nHjxjFhwgSmTp2KjY0NEyZMYOLEiUyYMIG2bdsCcPz4cZo3b86cOXOKPYCvOCEhITg6OuLq6qr13MrKigYNGtCgQQOtusGlmTFjBgsWLEClUpXaV61Wk5ycrHX9nVq3bk1ycjLr168HICAggA4dOqCrq0tiYmKRB0n6+PgQHBzMpUuXSE1NZfny5Xh6egLQs2dPVq5cSXx8PA8ePGDdunVKW9++fZk+fTqXL1/m4sWLfPrpp1ISQwghhBBCCCGEEKIcyrVzeejQoSQnJ/Pdd9/xwQcfYGlpyaRJkxg7diy//fbbq56j+Idp2rRpkWUxnhUZGcnq1avp2bMnJ0+e5JtvvuHq1au4uLiwadMm6tevT0BAAJGRka8kufzLL7/w6NEjpTxFUFAQx44dUw4RfFatWrV47733AOjYsSMnTpxg5MiRjBo1iooVK5Kbm1toZzLk7/J/tsxDz549lbIY7u7uAOTk5ODg4EDPnj0BqFixItu2bSvTGl4kET1//nxmzZpV5v6vm56eHmvXrqVv3774+/ujo6Oj/BuxsrIiPDycRo0aacU4OzszYcIEXFxcMDIyonbt2kp9am9vb7Zt20bt2rUBaN++PT169ABg5syZqNVqOnToQGpqKp07d1bqLwshhBBCCCGEEEKIsitXcvnQoUNcunQJe3t7dHR0UKlUDB48mNmzZ7/q+Yl/oNDQUOVAvwJ3797Vure1tWX58uWEhoZSuXJlpkyZwpgxY+jduzdOTk5Kv5ycHKWkxMsoGOPZsTZv3kxaWppWfd5Dhw5x/PhxJbkM+TV7C+oc79+/H29vb0xNTcnKyiI3N5fdu3eTkZHBm2++WWrJCrVazYEDB5Ta00+fPn3ptRXlk08+YfLkycp9cnIy9vb2r+VdZdW1a1du3LhBWFgY7u7u2Njk134u6bDIefPm0b9/f+Lj4/Hw8FCS9yqVio0bN+Ln50daWhoeHh7Kjm59fX0WL17M4sWLX/+ihBBCCCGEEEIIIf7BypWVe+utt9iwYQPTp09HpVKhUqk4ceIE9evXf9XzE/8AeXl5aDQaZYexq6trsTuX8/LyyM7Oxs7Ojv79+xMaGoqVlRVNmjQpNO6PP/7I6tWrCyWqXxU9PT2OHz+utXs5ISFBKYnxrB07dpCQkMDIkSPJysoCSq65DPD999+zadMmIL8OMOTXmR41ahRffPEFAMeOHWPcuHGvcllA/kGEBfWr/5dUqVIFLy+vF4qpV68e9erVK7Lt+ZIjQgghhBBCCCGEEOLVKVfN5W+++Ybly5dTrVo1UlJS6N27NxMmTCAwMPBVz0/8A4SGhtK8eXNatmzJhg0byMnJ4Z133tG6qlevzsyZM2nVqhUtW7YkMTGx2PEKdrLWrVuXwYMH8/3332u1Z2Vl8ejRI1JTU8s13z/++IN169ahUqmYMGEC58+fV65PPvmkUP+8vDxmzJjxQjuoNRoNgwYNIicnhzt37pCXlwdAVFQUb731Vrnm/UpkpkFa4uu9Mov+vkRFReHq6oqVlRX+/v4l7lguEBISgoODA3Z2dmzevFmrLTAwkMqVK1OrVi2OHDlSKPb+/fvY2NgQGhpa6nuEEEIIIYQQQgghRGFlzoaFhYVRo0YNbG1tcXV15fr16/z666/cuXOH6tWr4+XlhaWl5eucq/j/VLNmzfj999+B/ITe+PHjWbZsGXZ2dgAcOHCAzZs3s3TpUipUqFDqeDk5OdSuXRtnZ2caN25MXFwcwcHBDB8+HD09PXbt2kWvXr0YPHhwsbuGi5KdnU1ycjKdO3dm6tSpACxbtozg4GClT1E7lzdv3kx2djaDBw8u87uePaDOwMAAFxcXsrKyCAsLUw61K0p6ejoqlQpjY+Myv+uFxEWC/suXGSmNkYEBFc3/+/NCrVbj7e2Np6cnwcHB+Pn5sWHDBoYOHVrsGFFRUfTv35/AwECaNWtGjx49aNKkCU5OTuzfv5+pU6cSHByMra0tAwYMIDQ0VCm1AeDn54ePj4/sbhZCCCGEEEIIIYQopzJnkby8vDh+/Di2trbUq1eP0NBQ+vXr9zrnJv5hTpw4Qb9+/ejWrRvW1tbK8/r165OQkECDBg34/vvvadeundKWl5enJGL19fWJjY2lTZs2XLlyRenz66+/Mm/ePEaMGPFS8/vll19QqVSsW7eO1q1bM3r0aCZMmKAkmgFWr16tdWhlUlIS06ZNY8GCBahUKnJzc4s9YDAnJ4e8vDwMDAxo1qyZcgCftbU1P/30EyEhIdSoUYNq1appxRXUCgYYM2YMFSpU4Ouvv36ptRbn+OwlmJmbvZaxn1XR3JIatpWU+71795KUlMSSJUswMTEhICCAsWPHlphcXrt2LW3btsXX1xeAcePGsXHjRubOncuqVasYPHgw3bp1A6Bbt27s2LFD6fvrr79y6NAhYmJiXuMqhRBCCCGEEEIIIf7ZypxcTklJwcrKCoCrV68qf8YvRFl89dVXzJ8/n6CgIN5//32ttmrVqrF7926++eYbOnfuzKlTp3BxcQHyd7QmJycDMHz4cD755BMmTpyoFW9ubs5XX32Fjk5+lZeePXvyzTffEB8f/0JzHDx4MG3btmXPnj3ExcWRnZ2t1X7lyhVmzpyJv7+/8mzBggUYGhrSt29fTp48yXvvvYeBgQG6urpoNBo0Gg07d+4kOzubrKwsvL29+emnnwrtlk1LS+Pzzz9n7NixyrPAwEC2bt2qtdu2LDuxY2NjX2jdz2pU8w0sLCzKHV9ekZGRuLu7Y2JiAkDDhg2Jjo4uNaZTp07KvZubm3KoaGRkpNYvv9zc3Dhx4gS+vr5kZGQwduxYOnbsyO7du2nZsiW1a9d+DasSQgghhBBCCCGE+Gcrc3K5bdu2eHl58fbbbwPw4YcfYmBgUKjft99+++pmJ/4x+vbtS8+ePXFwcCi2z/jx43nvvfdwcnJSnv3nP/9Rvh4yZAhDhgwp9V1Pnz7l22+/ZdeuXcqznJwc3nvvPfr27VvsDmdDQ0Pq1q3L48eP8fHx4datWxgbG5Obm8uiRYs4deoUjRs35ujRo6SkpDBz5kxmzZpFz5490dXVZc2aNSxZsoSxY8fy+++/c/PmTXR0dLhw4YLyjoKk+fPi4+PRaDQsXbqU8ePHA1CjRg2aN2+u7LZ91vbt2zl9+jRLliwB8pPTxsbGSoId/rvrW19fv9TPrEDErRuvfefy87uWAZKTk5Wd3JC/W1tXV5enT58qv9R63vMxFhYW3L17t9S2ZcuWcefOHSwsLLh48SL+/v4sX76cvn37vrI1CiGEEEIIIYQQQvwblDm5HBwczIYNG3j8+DEqlQp7e3uMjIxe59zEP0hBfeXSPJtYLi8rKyt+++03rV9+LF68mPj4eBYsWECnTp2oXr16obi6devy4MED9PX10Wg0VK1alaysLGbOnMnVq1dxdHSkT58+TJ48WRlbX1+fZcuWERUVxe3btzl16hRnz54lPj6e4cOHc/jwYZo0acLAgQPx9PQsdodsnTp1GDVqFBs3blSeeXt707lz5yL/SiA9PZ0HDx6QnZ1NdnY2bm5uGBoacu/ePXR0dKhatSp5eXn4+voyZsyYMn92HjMmv/aay0YGBlxbtl4rwaynp4ehoaF2PyMj0tPTi00uPx9T0L+0tjVr1jB58mQWLlwIQNOmTZkyZYokl4UQQgghhBBCCCFeUJmzSGZmZowbNw6AWbNm8cknn/wtfz4vRFk8m1jeunUrCxcu5PTp0xw7dgxvb2/27NlD1apVtWIiIyMZPXo0q1atwtTUlCVLlnD69Gk++ugjxo8fj4ODAy1btuTmzZt07NhRifvuu++A/J3V7u7uVKtWjaVLlzJgwABOnDiBsbExRkZGXLp0iS5duhQ7Zx0dHSIiItDT++//lrm5ucyfP5+PP/4YAH9/fx4+fMjt27eJjY2lX79+VKxYkcuXLwP5CekRI0bQtWvX8n1wDs5gaVN6v/LKTCXz1gUepSRpJZetra2JiorS6pqSklLkX0c8G5OQkFBk/5La7ty5o/V9aNKkCffu3SM9PV0pyyGEEEIIIYQQQgghSleuLYqbN2/G1NT0Vc9FiFdKo9EQGBjIJ598QnBwMHXr1qVu3brExMTg5ubGsmXL6NGjh9LfxMSEsLAwVqxYwUcffcThw4eVwwULDum7fPkyBgYGNG7cGEDZOVyQuExJSWHSpEn88ssvpKenK2UqTp06RcOGDalcuXKJc27atCnnz5/XWkNWVpZyP3fuXPLy8vj555/Zt28fa9euRa1Ws3HjRhYsWEBMTAwxMTF8+umnmJmZaR0+WCZGpmBa4cViXgFXV1eCgoKU+1u3bqFWq7UOfiwq5uzZswwfPhyA8PBw5TDEgrb27dsXaqtevToZGRnKOHFxcVhZWUliWQghhBBCCCGEEOIF6ZTepbAPPvhASbYJ8b/o1KlTtGvXjlmzZnHw4EG8vLyUtqVLlzJjxgyGDh1KkyZNWLBgAUlJSeTk5ODn58fNmzdJSUnh1KlTDB48mMzMTCX20KFDdO7cGZVKBcCOHTto3LgxjRs3JjQ0lGnTpqGvr0+vXr1wdnZGrVYDsG/fPq3dsllZWWU6FFOlUmFoaKgkmAuS5QUOHz7MBx98QHJyMm3atCErK4tr166xe/dubty4Uey4BQclPnv9nVq3bk1ycjLr168HICAggA4dOqCrq0tiYiK5ubmFYnx8fAgODubSpUukpqayfPlyPD09gfxDHVeuXEl8fDwPHjxg3bp1Slvfvn2ZPn06ly9f5uLFi3z66adSEkMIIYQQQgghhBCiHF5vcVUh/gZxcXF06tSJPn36kJWVhaenJyqViszMTDQaDcbGxuTl5eHk5ETHjh3ZuXMn7u7udOvWTSlJsX37dvT19XFycsLBwYHWrVsDEB0drVXLt3fv3vTu3Zu0tDQ++OADunfvzrx585T20aNHA3D9+nXatGmjPPf09OTEiRNKkhrydynn5eVplcUoeG5lZcWjR4/Q09OjQoUKSpuhoSGGhobKDumtW7eyZcsWvvrqqxJ/ATR//nxmzZr1gp/s66Onp8fatWvp27cv/v7+6OjocOzYMSC/hnZ4eDiNGjXSinF2dmbChAm4uLhgZGRE7dq1lfrS3t7ebNu2Talx3b59e2WX+syZM1Gr1XTo0IHU1FQ6d+6s1F8WQgghhBBCCCGEEGUnyWXxj+Pg4EBsbCw2Ntq1g2fOnMmjR49YsWKF1vM5c+YAkJiYWOyYEydOBGDBggW4ubmxfv16hg4dCsDFixcZMmQIly5d4v79++zfvx/4by1mgLVr1+Lu7o6rqystW7bk8OHDSkK4wNdff82mTZsIDQ3VSjoDyu5plUqFRqNBrVaTlpbGnTt3UKlUSv+8vLwyHbT5ySefMHnyZOU+OTkZe3v7UuNep65du3Ljxg3CwsJwd3dXvn8ajabYmHnz5tG/f3/i4+Px8PBQypOoVCo2btyIn58faWlpeHh4KJ+Rvr4+ixcvZvHixa9/UUIIIYQQQgghhBD/YJJcFv9INjY25ObmolKpCiVxC+Tl5WntFI6IiMDb21trx2+1atU4ffq0cm9lZcV//vMfevXqRd++fTl48CCDBg0iNzeXW7duUb16dQDatGmjlMQAqFixIosXL8bf358zZ84UOyeAAQMGYGRkxJw5c7CzswNQEsY5OTksW7YMAwMDNBoNMTEx1KxZU0nApqenU6VKFWV9xSnY8fy/pkqVKlolTMqiXr161KtXr8g2V1fXVzEtIYQQQgghhBBCCFGEctVcFuL/B2vWrMHBwQFHR0ccHR35+uuv+f7775V7BwcHvvnmG6V/Xl4ehoaGxMbGEhsbS0hICI8fPy40buPGjXn69Cm3b9+mU6dOXL58mVq1atG3b186dOhAhw4diIyMLFTeol69ely6dKnUea9atQorKyvq1q3LggULtA70mzRpEomJiSxfvhwvLy+2b99Op06dyMnJAfIT5AWlILKzs1/8Q8tMg7TE13dlphb52qioKFxdXbGyssLf37/E3coFQkJCcHBwwM7Ojs2bN2u1BQYGUrlyZWrVqsWRI0cKxd6/fx8bGxtCQ0NLfY8QQgghhBBCCCGEKJrsXBb/WB9++CEffvihcl9cWYwC+vr6hZ49X7d48ODB7N27l7p161KrVi309PSU3cWbNm2iWrVqQH6N32dNnDiRTZs20b9//xLnrNFosLCwYPHixXTr1o1PPvkEHx8f3nzzzSL7P378mAYNGuDg4MDdu3fp3r07P//8M6dPn+bHH38s8V1FiosE/df7Y8HIwICK5pbKvVqtxtvbG09PT4KDg/Hz82PDhg1K2ZGiREVF0b9/fwIDA2nWrBk9evSgSZMmODk5sX//fqZOnUpwcDC2trYMGDCA0NBQrTIpfn5++Pj4yM5mIYQQQgghhBBCiJcgyWUh/k9OTg6xsbFKaYvs7GysrKwAyM3NBaBHjx507txZ6/C/gr6enp7Ks1u3bpGTk6PsHh44cCC+vr40aNCg2Pfn5uYqO5ABWrVqxalTp4rse+/ePfbu3cuJEydYt24dRkZGTJkyhcmTJ6Onp8dHH33E0KFD6dixY6H6zSU5PnsJZuZmZe5fHhXNLalhW0m537t3L0lJSSxZsgQTExMCAgIYO3ZsicnltWvX0rZtW3x9fQEYN24cGzduZO7cuaxatYrBgwfTrVs3ALp168aOHTuUvr/++iuHDh0iJibmNa5SCCGEEEIIIYQQ4p9PksviH2nChAls3boVAwMDJbmanp6ORqNh9+7dQP4hecnJyQQFBdG/f39UKhXNmzfn5MmTQP5BfQU7nwsO1CtIWD5PrVZz7NgxrZrLzyaXmzZtWuqcC+Zz6tQp6tSpQ6VKlYrtGxkZybvvvsvq1au5ceMGzs7OTJo0iREjRmBgYEBoaCjt27fnrbfeKnW39LMa1XwDCwuLMvd/FSIjI3F3d8fExASAhg0bEh0dXWpMp06dlHs3Nzdmz56ttPXr10+r7cSJE/j6+pKRkcHYsWPp2LEju3fvpmXLlkoZESGEEEIIIYQQQgjxYiS5LP6Rli1bxrJly0rtl5WVpRx816hRIyWxDPlJzoLD/IKCgkoc5+LFixgbGyv3x44dA+D7778vNkaj0ZCVlaUcrPfZZ5/x2WefUatWLcaPH8+kSZOK7fv222/z+++/Y2ZmRsOGDTly5AhOTk706dOHOnXqMHv2bM6cOYOlpWWR7y5OxK0br3Xn8vO7lgGSk5OpWbOmcq9SqdDV1eXp06fKzvHnPR9jYWHB3bt3S21btmwZd+7cwcLCgosXL+Lv78/y5cvp27fvK1ujEEIIIYQQQgghxL+FJJfFv5qBgcErGadg1+2LuHPnDk2bNsXY2LhQ6Yrnk+N5eXlYWFgQFRUFgLGxsZJoTk9Px97enszMTIYOHcrJkyfJzMzEwMCApKQkLCws0NEp29mdHjMmv9aay0YGBlxbtl4rwaynp6esRelnZER6enqxyeXnYwr6l9a2Zs0aJk+ezMKFC4H8HeVTpkyR5LIQQgghhBBCCCFEOUhyWYi/ib29PQ8fPnyhmNzcXHJzc1GpVOjo6JCRkcH48eM5ePCg1uGDmzZtQqPRoFarCQ0Nxd7evmwvcHAGS5vS+5VHZiqZty7wKCVJK7lsbW2tJM0LpKSklJj4t7a2JiEhocj+JbXduXOHLl26KG1NmjTh3r17pKenl+sXBEIIIYQQQgghhBD/ZpJcFuJ/gK6uLnXq1NFKEAM8ffqUzp07K2U5fvrpJ8aPH09KSgoqlYp9+/YRFxeHoaEhZ86cwc3NDT09PeLi4rCzs0NfX//FJmJkCqYVXtGqysbV1VWr7MitW7dQq9VYW1uXGHP27FmGDx8OQHh4ONWqVdNqa9++faG26tWrk5GRoYwTFxeHlZWVJJaFEEIIIYQQQgghykGSy0L8DzA0NOTTTz/F3Nxc6/n+/fu1Smb06tWLXr168dZbb+Hu7s6GDRsAOHLkCF26dOGXX36hffv2zJgxg2vXrrFt27Yidy2r1WrUarVyn5yc/HoWVgatW7cmOTmZ9evXM3ToUAICAujQoQO6urokJiZibm5eKOnu4+NDy5YtmTBhAjVr1mT58uUMGDAAgJ49ezJ69GiGDh2Knp4e69atU0qM9O3bl+nTp1O9enVyc3P59NNPpSSGEEIIIYQQQgghRDlJclmI/wFLly4lLS2NtLQ0refOzs7UrVtX61l4eDjXrl3D3t6eH374gZo1a/L+++/z448/Krt1169fz/jx4+nWrRuhoaGFkrPz589n1qxZr3dRZaSnp8fatWvp27cv/v7+6OjoKAciWllZER4eTqNGjbRinJ2dmTBhAi4uLhgZGVG7dm3GjBkDgLe3N9u2baN27doAtG/fnh49egAwc+ZM1Go1HTp0IDU1lc6dOyv1l4UQQgghhBBCCCHEi1FpNBrN3z0JIf6tRo0axenTp8vUt3v37sydO5cRI0Zw/PhxatSowblz5zh8+DD37t3j9u3bjB8/HoAJEybg5eVF06ZNsbEpXEO5qJ3L9vb24P8pWFd5NYt7XloiXDlB2MKVNKlVu1Dz/fv3CQsLw93dvcg5FyU6Opr4+Hg8PDwK1WgODQ0lLS0NDw+PQgcmCiGEEEIIIYQQQojiJScnY2lpSVJSEhYWFsX2k+SyEH+jrl270q9fP/r06VNiv8WLF3Pz5k0GDRpEmzZt+OSTT7h16xadO3emVatWWFhY4OjoyMmTJwFo3LgxV65cwdHRsUzzKPiB8Xcml4UQQgghhBBCCCHE/4ayJpd1/sI5CSGeo6Pz3/8FW7RoQYMGDXBxccHFxYU333yT999/X6vvlStXGDJkCJUrVwagd+/eVK1aFVNTUz777DNGjhzJiBEjmDZtWpkTy1oy0/KTwK/jykzVelVUVBSurq5YWVnh7+9PWX7PFRISgoODA3Z2dmzevFmrLTAwkMqVK1OrVi2OHDmiPH/8+DEqlUrr2rRp04t+MkIIIYQQQgghhBDiOVJzWYj/Eebm5nz77be89dZbAOzcuZMff/xRq8/QoUPp06cP3333XaH4oUOH8uWXX5KXl8e+ffvKN4m4SNB/fT8WjAwMqGhuiVqtxtvbG09PT4KDg/Hz82PDhg0MHTq02NioqCj69+9PYGAgzZo1o0ePHjRp0gQnJyf279/P1KlTCQ4OxtbWlgEDBhAaGoqNjQ1hYWG0atWKXbt2KWOZmpq+tjUKIYQQQgghhBBC/FtIclmIv1FeXp7ytZ2dHQMGDNBqb9OmjdKvoG6wsbExOTk55OTkAJCamkpwcDCzZs2ia9euPHnyhCZNmjBlyhS8vb2pWrVqmedzfPYSzMzNXnJVxatobkkN20rs3LmTpKQklixZgomJCQEBAYwdO7bE5PLatWtp27Ytvr6+AIwbN46NGzcyd+5cVq1axeDBg+nWrRsA3bp1Y8eOHfj6+hIaGkrLli2pUKHCa1uXEEIIIYQQQgghxL+RJJfFK/XVV19RqVIlBg4c+NrekZeXR25uLvr6+qX2LUjA6ukV/089OzubrKysv2U367OH6q1fv77IPoGBgaxfv5558+Ypz7Kzs8nMzOTs2bO0a9eO1q1bs2nTJjw8PAD45ZdfWLFiBd988w0nT54sc2K1Uc03Sqyj86pERkbi7u6OiYkJAA0bNiQ6OrrUmE6dOin3bm5uzJ49W2nr16+fVtuJEyfw9fXl999/5+rVq3zzzTdYWVkxbdo05eBDIYQQQgghhBBCCFF+klwWpcrJyeG9996jb9++jBgxotg+enp6NGvWDB8fH3x8fDA2NiYvL49FixZx6tQppa+LiwszZ84kKysLQ0NDrKystGoPFyU5OZlFixYxYcIETpw4Qdu2bdHR0VF28wLk5uaiq6ur3Gs0GvLy8li1ahWjR48uduwrV67QunVr/vzzT9q1a8fatWtxdnYu68fzUnbv3o2BgQHe3t6YmpqyatUq2rVrp5Vozs3N5ddff6VWrVoAnDp1iu+++46IiAggf52PHz9mypQpSsylS5e4cuUKNWrUKDGx/ryIWzde+c7lgt3Kz0pOTqZmzZrKvUqlQldXl6dPn2JlZVXkOM/HWFhYcPfu3VLbrl+/zpAhQ+jfvz/nzp1j0KBBuLq64u7u/srWKIQQQgghhBBCCPFvJMllUarFixcTHx/PggUL6NSpE9WrVy/Up27dujx48AB9fX00Gg1Vq1YlKyuLmTNncvXqVRwdHenTpw+TJ0/GwMAAAAMDAwwNDblw4YJy+FxGRgbGxsbKuFlZWRgYGNClSxfMzPKTnq1bt0atVivjQP5uZkNDQ5KSkpTdsJCfmC04KO755HMBPT09zM3NMTc356uvvmLVqlWsXLmyUMK7Ro0ajBs3jmnTpinPHB0diYuLA6BKlSoMHDiQgIAA9PT0Smy7f/8+7dq1U3ZLt2zZkj59+vDNN9/Qu3dvFixYwKNHj4iNjeWdd95h5syZyjuNjY0xNDTk8uXL1K9fX+vzepaRkdELJZYBPGZMfuU1l40MDLi2bL1WgllPTw9DQ0PtfkZGpKenF5tcfj6moH9pbZcvX1ae16hRg7179xISEiLJZSGEEEIIIYQQQoiXJMllUaKtW7eycOFCTp8+zbFjx/D29mbPnj2F6vhGRkYyevRoVq1ahampKUuWLOH06dN89NFHjB8/HgcHB1q2bMnNmzfp2LGjEqenp8cff/zBb7/9Rp8+ffj6668JCwsjJCQEgC+++EJJ8hYkhnV0dLQSywAPHz7E1NRUK7H8bAzAxIkTCQ4OLlT+Ijc3l7t37yoJ7pycHIKDg4mPj1f6XrlyhT///JMDBw5oJZcBNm3aRKdOnfjjjz8YNGgQ1apVY8KECSW2ValSRSkDoVKp+O233+jfvz/z58/HxsYGfX19LC0tiYyM1EpCb9myhdTUVDIyMmjbti3Xr19HT0+PL7/8UmtOAwYMUJLqL8TBGSxtXjyuOJmpZN66wKOUJK3ksrW1NVFRUVpdU1JSCn1fn2VtbU1CQkKR/Utqe16lSpWUpL8QQgghhBBCCCGEKL+SaxGIfy2NRsOKFSsYPnw4GzdupG7dunz44Ye0adMGNzc3fvrpJ63+JiYmhIWFsWLFCgAOHz5MixYtgP8meC9fvoyBgQGNGzfWijU0NGTChAnExcVx7NgxWrdujYuLCykpKRw7dowmTZoUOcfx48fj6OiIo6MjLi4upKamKveOjo6F4r755hsSEhKIjY3Vuq5evYqurq5yf+fOHRITE7WS0AcPHsTDw4PTp0+TkZGhNa6pqSnW1tY0a9aMkSNHsmfPnlLb0tPTyczMVA7027FjB0+ePKFv375kZmYqCfUjR47g7e2tjLdq1SpiY2MxMTHh3XffZdeuXfTu3ZuQkBCtq3v37iUmaotlZAqmFV7dZVR0iQ1XV1fOnj2r3N+6dQu1Wo21tXWxU3s+Jjw8nGrVqpXYFhcXR8uWLbUS7WfPnsXBwaFsn4cQQgghhBBCCCGEKJYkl0Uhp06dol27dsyaNYuDBw/i5eWltC1dupQZM2YwdOhQmjRpwoIFC0hKSiInJwc/Pz9u3rxJSkoKp06dYvDgwWRmZiqxhw4donPnzlp1kiG/VMH06dMZO3YsERERjBw5ktq1a/Ppp58SExNDly5dipxnUlISAwYMUBLCOTk5SoJ4w4YNPHjwoFDMoEGDtBLQkydPxtTUFAMDA548eQJAQEAAkZGRWnEHDhyge/fuVK9enRMnThT72enp6ZGVlVVqW8Hn5+zsTNWqVRk5ciSPHz/G2dmZjz76CMgv9XHw4EFl/Tk5OURERCiH9gUEBLB+/XrOnTvH+fPnC12dOnXi4cOHRc5FrVaTnJysdf2VWrduTXJyslJbOiAggA4dOqCrq0tiYiK5ubmFYnx8fAgODubSpUukpqayfPlyPD09AejZsycrV64kPj6eBw8esG7dOjw9PalRowYPHz7k008/JSwsjE8//ZTffvuN4cOH/6XrFUIIIYQQQgghhPgnkuSy0BIXF0enTp148803qVOnDp6enlSoUAEjIyMMDQ2pUKECU6ZMoU6dOnh5ebFz504iIiKoWLEin332Gdu3b6dmzZro6+vj5OSk7F4GiI6OLlRnt8CHH35IbGwsHTt2xMjIiC+//JI1a9bw/vvvFxvzbE3ky5cvK4nEAs8nsSE/Ib169WpiY2OZOXOmklR94403uHnzJklJScybN0/ZUQyQnZ3N8ePHad68Oc2bN+fAgQNFzufBgwf88MMPSvK3pLYtW7YQHR3Nt99+i7m5OYcPH+bixYtER0ezbNkyAO7fv09eXp6yjj/++ANXV1cqVqwIgIODAzdv3uT8+fM0atSIxYsXM3HiRLp06cL58+dJTU0tcp4A8+fPx9LSUrns7e2L7fs66OnpsXbtWsaNG0fFihX5+eefWbBgAQBWVlZcunSpUIyzszMTJkzAxcWFatWqoaury5gxYwDw9vamffv21K5dm5o1a9K4cWN69OiBSqVi+/btHDx4kBYtWrBv3z4OHDhA7dq1/9L1CiGEEEIIIYQQQvwTSc1locXBwYHY2FhsbLTr7s6cOZNHjx4pZS8KzJkzB4DExMRix5w4cSIACxYswM3NjfXr1zN06FCtPhqNhszMTEJDQ8nKysLW1pYKFSoUOlSvOAW7XStVqlRiv5ycHK37gh2yzs7OhIeH88svv/D+++9rle44c+YM2dnZNG7cmBYtWrBy5UqtMfr374+uri5paWn06NEDf3//Uts0Gg1r165l4sSJmJubK0nSWrVqsXXrVgDs7OxYuXIlXl5e/P7779StW5eDBw8SERGhjK9Wq3FxcSEuLo6TJ0+SnZ1NZmYmu3fvJi4ujuzs7CI/h08++YTJkycr98nJyX95grlr167cuHGDsLAw3N3dlX9zJdWKnjdvHv379yc+Ph4PDw+l9IdKpWLjxo34+fmRlpaGh4eHkpRv2LAh58+ff/0LEkIIIYQQQgghhPiXkeSyKMTGxobc3FxUKlWxyd28vDzy8vLQ08v/JxQREYG3t7fWAXrVqlXj9OnTyr2VlRX/+c9/6NWrF3379sXIyEhpCwoKokGDBjx69IhvvvmGJ0+e4OzszI8//qiVBH1+DgViYmJwdXUttr2AWq1m8ODBGBsbk5qaqpRVaN26NevXrycmJqZQIvLAgQNkZWVRqVIlcnJySEtL4/79+1SpUgXILxXi6elJpUqVMDY21ootrq1Pnz6cPHmS5s2bc+jQIQBiY2Pp2rWrVnyvXr344Ycf2LBhAyNHjiy0ntjYWPLy8jA0NCxyp3ZxDA0Ni90R/leqUqWKVtmVsqhXrx716tUrsu35fwNCCCGEEEIIIYQQ4vWR5LIo0po1awgICFCSxYmJieTl5bF7924gf8fv5MmTmTRpEoCS4Lx+/ToA58+fZ8CAAYXGbdy4MU+fPuX27dvUqVMHgIcPHzJr1iwOHz5MdnY2Fy9eZM6cOVy8eJH58+fz5ZdfFjlHtVqtfL1lyxa8vLxITk7GyMgIMzMzZfxnFSRyIX+HbFRUFHFxcXTu3JkRI0Ywb968Qoe9HTx4kClTpjB27FgA3NzcOHjwIAMHDgSgUqVKxR4QV1zb0qVLuXv3Lp6ennTo0AGAzMxMJVn/rHr16hVZJgJg69at+Pv7k5WVpZR6SE9PJzo6mp9++qlQsloIIYQQQgghhBBCiFdFai6LIn344Yf8+eefygF5EydOZNCgQcr9n3/+qSSWAfT19QuN8ewuZoDBgwfj5ORE3bp1qVWrlvJ8165dDBs2jPr16+Ps7My+fftYtGgRNWrUYOHChQQFBRU5x02bNjFz5kwWLVrE5cuXGTJkCPPmzaNevXrcunWLY8eOafW/f/8++/btY968eXTp0oXKlSszcOBA4uPjmTp1KjY2Nty+fRuAo0eP8uTJE548eUJYWBjdu3dXDgFs165dsXWXy8rOzg49PT0aNWrEvn372LdvH999951Wn4cPH+Lm5kZgYCA9evQocpwBAwYQHR2Nk5MTAwcOZM2aNVhZWfHDDz+UL7GcmQZpia/uyiy67nNUVBSurq5YWVnh7+9fYimMAiEhITg4OGBnZ8fmzZu12gIDA6lcuTK1atXiyJEjyvPHjx+jUqm0rk2bNr3AByKEEEIIIYQQQgghiiM7l8UrkZOTQ2xsLNWrVwfyD8GzsrIC/lvXuEePHnTu3Jlu3bopO3Rzc3Px9fXF0dERyK+d++OPPyrjZmVlce3aNW7evKmVrE5LS+PgwYMsW7aMP//8k8OHD2Nubs6CBQto2bIlkyZNYs2aNQQFBSljf/vtt3z//fd4e3vj5+dHixYtiI+PZ/DgwbzxxhtER0fj7OyMh4cHixcvpk+fPjg6OmJiYoKbm5vy7vbt2zNjxowyJURLkp2dzblz52jUqJFyX1CqIjs7m0qVKjF9+nRatmyJtbW11mdS8JkW3A8ePFip5zxw4EDq1KlDeno6JiYmLzapuEjQf7U/FowMDKhobqncq9VqvL298fT0JDg4GD8/PzZs2FCoDvezoqKi6N+/P4GBgTRr1owePXrQpEkTnJyc2L9/P1OnTiU4OBhbW1sGDBhAaGgoNjY2hIWF0apVK3bt2qWMZWpq+krXJ4QQQgghhBBCCPFvpdK8bIZM/ONMmDCBrVu3YmBgoNTxTU9PR6PRKIm5zMxMkpOTCQoKon///kRERDB+/HhOnjwJwMWLF/nwww85ffo0I0aMwMnJialTp2q9JysrC0NDQ27duqUkgJ939+5dnJ2dcXZ2Zv369djb23Px4kVcXFywt7dn9OjRjB07tlASNT09HT8/P2JiYjhx4gSQX7rj2RrSERERtGvXjpkzZzJ+/HhUKhUnT56kS5cuWFlZERkZiaWlJa/LqVOnmDlzplbN5Y4dO1K9enWlREhRZTJOnjzJuHHj+PHHH+nduzfVq1enQYMGfPLJJ5ibm3Pw4EH279/PmTNnWLNmDU2bNi11LsnJyVhaWnI84gJm5mavdJ0VzS2pYfvfgxZ37tzJsGHDuHPnDiYmJkRGRjJ27FhOnTpV7BgTJ07k6tWr7Nu3D4Bly5aRkJDA3Llz6d69O1WqVGH16tUATJo0ifr16+Pr68u8efNITU1l/vz5r3RNQgghhBBCCCGEEP9kBbmipKQkLCwsiu0nyWVRbllZWeTl5WkdzPdXuXnzplZpjeKkpqZiZlZ8sjQpKalQAjkpKQldXd0S416FnJwc5f3PJpF9fHyoVKkSq1atUp7l5eWRmZlZ5E7khQsXsm7dOi5evFjuQ/peV3L5+cQywKxZszh37hx79uwB8mtf29jY8OTJk2LHadu2LZ06dWLatGkAnD17ltmzZ7N3715q1qzJggUL6N27NwCbN2/mxIkTrFq1im7dunH16lXi4+OxsrJi2rRpjB8//pWtTwghhBBCCCGEEOKfqKzJZSmLIcrNwMDgb3t3WRLLQKkJ4qJ2Jr/O3crPSkpKolq1ahgZGRW5Q3nbtm3K1wXJ5YId5AU7yjMyMli6dCnr168vlFjOzc0tVPe6NB4zJr/SshhGBgZcW7ZeK8GcnJxMzZo1lXuVSoWuri5Pnz5VSqk87/kYCwsL7t69W2rb9evXGTJkCP379+fcuXMMGjQIV1dX3N3dX9kahRBCCCGEEEIIIf6tJLksxN/ExsaGzMzMF47z9fVlx44d6OjokJ6eTnZ2NgMGDNDqk52dTWpqKnFxcUod7DJxcAZLmxeeU5EyU8m8dYFHKUlayWU9Pb1CiXAjIyPS09OLTS4/H1PQv7S2y5cvK89r1KjB3r17CQkJkeSyEEIIIYQQQgghxCsgyWUh/mZ5eXlUrly5xAMC7969q+wUX7duHevWrePevXvUrVuXX3/9lZYtW5Kamqp18F+5GJmCaYWXG6MU1tbWREVFaT1LSUkpcSe8tbU1CQkJRfYvqe15lSpVIi4u7mWmL4QQQgghhBBCCCH+j07pXYQQr5OOjg7JyclERETw6NEjrSsqKorHjx+jr69fKG7EiBH079+ftm3bcuDAAerXr1/md6rVapKTk7Wuv4qrqytnz55V7m/duoVarS4xMf58THh4ONWqVSuxLS4ujpYtW2ol7c+ePYuDg8OrXI4QQgghhBBCCCHEv5Ykl4X4H5Cbm1tie0GNZYDMzEw+/PBDYmJiWLRoEZBfCuLZ3bo5OTmkpaUVO978+fOxtLRULnt7+5dcQdm1bt2a5ORk1q9fD0BAQAAdOnRAV1eXxMTEIj8LHx8fgoODuXTpEqmpqSxfvhxPT08AevbsycqVK4mPj+fBgwesW7cOT09PatSowcOHD/n0008JCwvj008/5bfffmP48OF/2VqFEEIIIYQQQggh/slUmpL+Fl8I8drl5OSgr6+PlZUVOjrav+/RaDQ8efIEtVqtJI8TExOpUaMGJiYmGBkZAfkJ50ePHin1lfPy8tDT0+PmzZtFvlOtVqNWq5X75OTk/ASz/6dgXeXVLCwtEa6cIGzhSprUqq3VtGvXLvr27YuxsTE6OjocO3aMevXqoVKpCA8Pp1GjRoWG++yzz1i8eDFGRkbUrl2bkydPYmxsjEajYdCgQWzfvh2A9u3bs2vXLlQqFRcvXmTYsGFcunSJ+vXrs3TpUjw8PF7N+oQQQgghhBBCCCH+oZKTk7G0tCQpKQkLC4ti+0lyWYj/AY8fP+bEiRO8//77LF68mIiICDZt2kRoaCguLi5aO5chP+mcl5eHrq4uAMeOHWPIkCHExsaW6/0FPzD+quQywP379wkLC8Pd3R0bm7IdIhgdHU18fDweHh6F6iqHhoaSlpaGh4dHoc9LCCGEEEIIIYQQQpRdWZPLcqCfEH+z1NRUunbtiq2tLe+//77yXK1W06dPH95++202btyIubm50qZSqZg5cyb3798nKChIa7zPPvsMHR0d5syZ85etoTyqVKmCl5fXC8XUq1ePevXqFdnm6ur6KqYlhBBCCCGEEEIIIcpIai4L8Te6e/cubdq0oVKlSmzdulWrzdDQkLNnz/LgwQPc3d21diVv3bqVr776Ch8fn0Jjdu/enRUrVjB58uQXn1BmWv6O41dxZaZqDR0VFYWrqytWVlb4+/tTlj+aCAkJwcHBATs7OzZv3qzVFhgYSOXKlalVqxZHjhwpMv7MmTPUqlWrrKsXQgghhBBCCCGEEC9Adi4L8Tfq378/derU4fvvvycrK4vIyEhCQ0PzS1QAlSpV4siRI/Ts2ZMffviBzz77jG3btjFs2DBCQkLo2LEjAElJSUopCFdXVw4cOEC7du0wNTV9sR3McZGg/+p+LBgZGFDR3BK1Wo23tzeenp4EBwfj5+fHhg0bGDp0aLGxUVFR9O/fn8DAQJo1a0aPHj1o0qQJTk5O7N+/n6lTpxIcHIytrS0DBgwgNDRUq7xGdnY2I0eOJC8v75WtRwghhBBCCCGEEEL8l9RcFuJv9OTJEypUqICOjg7Z2dk0bNiQihUr8tVXX+Hm5qb0y8rKUmoMf/jhh7z77rv06NEDgG7durF//358fHz44YcflJhDhw5ha2uLs7NzqfMoqKNzPOICZuZmr2x9Fc0tqWFbiZ07dzJs2DDu3LmDiYkJkZGRjB07llOnThUbO3HiRK5evcq+ffsAWLZsGQkJCcydO5fu3btTpUoVVq9eDcCkSZOoX78+vr6+SvycOXPYvHkz6enp5a5FLYQQQgghhBBCCPFvVNaay1IWQ/zj5OTkKF+np6cTHh6u1X706FHu3btXprE0Gg1paWmvdH7Psra2Rkcn/39DfX19rly5wsmTJ7USy4DW4XWrVq1SEssAM2fO5PTp02zatEkrpkOHDmVKLL8OFc0taVKrNjVsKwEQGRmJu7s7JiYmADRs2JDo6OgSx4iMjKRdu3bKvZubG2FhYaW2AcTExPD111+zYsWKV7YmIYQQQgghhBBCCKFNymKI/3kajQYdHR2ioqKoX79+iX3VajWNGzdmzpw5+Pj4EBsbS9euXbl48SJWVlYADBs2jEWLFtGzZ89S352dnY2ZmRmxsbHExsYSFxfHoEGDlPasrCwgPzFcUJbiWX/88Qf79u3jhx9+YN68ebRv3/6F133p0iUaNGhQbL+bN28yb948QkND0dXVLfP4RfGYMfmVlMUwMjDg2rL1SnI5OTmZmjVrKu0qlQpdXV2ePn2qfF+e93yMhYUFd+/eLbUNYNSoUXz++edSb1kIIYQQQgghhBDiNZLksvifp1KpMDQ0xMjICMjfefzw4UOioqK4ePEiFy9e5NGjRzRv3pzvv/+eoKAgevbsibOzM/Xq1cPf319JYl67do24uDiioqKIjo5W6vKuXLmSNWvWYGZmhkqlIi0tjfj4eAwMDDAwMMDExITatWszZswYGjVqRMOGDYH8Ug3Lly8nMzMTlUpFbGwsfn5+XLx4kRs3bpCcnEyjRo3o3r27skMZ8ks2zJkzBxMTE3JzczEwMODx48eF1q2np6e1a7kourq6JCUlvXRiGQAHZ7C0Kb1fSTJTybx1gUcpSUpyWU9PD0NDQ61uRkZGpKenF5tcfj6moH9pbevWrSMjI4MJEyZw+/btl1uLEEIIIYQQQgghhCiWJJfF/yyNRoNarcbQ0BBdXV1UKhVqtZotW7bwxx9/oFKpiI6OxtDQEFdXVzIzM3n8+DEtW7YkJiaGKVOmcPToUYyMjPjuu+8wNjamffv2dO3alTfffJPc3Fyys7MxNDRk/vz5zJ8/H4DHjx/zxhtvKEldKysrsrKyqFatGufOnePs2bNcvHiRhg0b4u/vj7+/P+PGjaNy5cqYmJgwdepUdHR0ePPNN+natSs9e/ZkyJAhWmvT19end+/ebNq0ifPnz+Pt7c3hw4c5c+YMurq6SiJapVKxZs0aatSogZ+fX5Gfk46ODhUqVHg1H7qRKZi+orGeYW1tTVRUlNazlJSUEhPn1tbWJCQkFNm/uLaHDx/y+eefc+jQIa1kvhBCCCGEEEIIIYR49SS5LP5nxcXFUadOHUxMTEhPT6dJkybk5uayf/9+WrRoAcCQIUOoXr06c+fOBfLLYoSFhdG0aVPWrFnDyJEjadGiBUOGDOHJkyfUq1ePo0ePUrdu3ULvu3r1Km+99RZ37tyhevXqANy+fRtjY2M++eQT/vjjD65cuUKDBg2YNm2asnv56dOnbNu2jcuXLwOwZcsWzp07x549e4pdm56eXqH7ypUrU7duXaXERkHpCCcnJ2U+jx494smTJ5iZmSnJ00ePHqGnp8f9+/eB/KR8RkYG6enp1KxZE1NT03J/D14VV1dXgoKClPtbt26hVquxtrYuMebs2bMMHz4cgPDwcKpVq6bVVlBmpKBt7969JCQk0LJlSwDy8vJITU2lQoUKXLx4kRo1aryuJQohhBBCCCGEEEL860hyWfzPcnR0VGoam5mZERERgaOjY4kxv/32G97e3owfP56ZM2eSm5urtIWFhVGnTh1atWqlPGvZsiU///wzmZmZdOzYkcDAQLKysqhTpw4dO3bk/PnzqFQqTExMCAwMpFq1alSuXFnrndOmTaN79+5UrFgRyC/RUHBwHcBXX33FDz/8QJ06dQgMDATydxtv3bqV3bt3k5ubi7W1NQ0aNMDW1pa8vDyqVq0K5Je8ePfdd5V1b926FX9/f/T19ZXxs7KyUKvVvPXWW8qznJwc1Go1p06dolmzZoU+J7VajVqtVu6Tk5NL/FxfVuvWrUlOTmb9+vUMHTqUgIAAOnTogK6uLomJiZibmxcq6+Hj40PLli2ZMGECNWvWZPny5QwYMACAnj17Mnr0aIYOHYqenh7r1q1j2bJleHp64uHhoYxx584d+vTpw6lTp7Czs3utaxRCCCGEEEIIIYT4t5G/Gxf/X7l69Sp5eXnFtnt4eHD58mWuXr1KYmIi2dnZTJs2DSsrKw4ePMjRo0e5d+8eV69exc7Ojo4dOwL5CeEtW7YwfPhwfv75Zxo3bsy3335LQkICvr6+1KpVi0aNGtG0aVN+/PFH5X0ajYZTp05x7NgxjI2NOX36NLq6ulrJZRcXF3r27Em7du2UZzo6OvTu3ZvExESOHj2qHAY4depUPvvss2LXN2bMGNLS0khMTFQuf39/TExMuH//vvIsNTWV7OzsIhPLAPPnz8fS0lK57O3ty/YNKCc9PT3Wrl3LuHHjqFixIj///DMLFiwA8suOXLp0qVCMs7MzEyZMwMXFhWrVqqGrq8uYMWMA8Pb2pn379tSuXZuaNWvSuHFjevTogZmZGY6OjspVvXp19PT0cHR0LLRbXAghhBBCCCGEEEK8HEkui/95sbGx5Obm4uXlRffu3bV23BbF3t6e7du3Y2trS2JiIhs2bOCjjz7C2NgYXV1d9PX1GTFiBD4+Pnz44YdKXLNmzRgzZgzfffcdrVu3xs7ODpVKRePGjQkLC+OXX35BV1eXnj17KjFZWVns3buXixcvYmpqStOmTQG06v16eHgwatQofHx8lGfFJcinT5/Opk2buHHjRpk/n19++QVzc3O+++67Msd88sknJCUlKdeff/5Z5tjy6tq1Kzdu3OC7777jypUr1KtXD8hP0Ddq1KjImHnz5hEeHk5ISAhnzpzB2NgYyK9FvXHjRo4fP86ePXvYtWuXkqB/lqOjI7Gxsa9rSUIIIYQQQgghhBD/apJcFv+zwsLCcHJy4p133iE7O5uvv/6aq1evKgnG4jx+/Bg3Nzdyc3N5+vSpctidSqWia9eu1K1bl8OHD7N27Vpq167NyZMnldgGDRoAcPjwYeVZu3btOHDgADNmzODzzz/XOoTuwoULtG3blvXr1+Pi4oKRkZFWKY5nPZsUf76PRqMBoE6dOgwZMoQHDx6U4ROCQ4cO8eDBA3bu3MkXX3zBo0ePyhRnaGiIhYWF1vVXqFKlCl5eXtjY2JQ5pl69erz77rtFHv7n6upKmzZtikwsCyGEEEIIIYQQQojXS5LL4n9WvXr1WLx4Mbdv38bIyIjatWuXKe7YsWNKDd+YmBjq1KmjtO3atYsrV67Qrl07Fi1axB9//KHUYM7Ozubjjz9m1qxZBAYGEhUVBUDFihWpVq0aBgYGyuFyBZo3b06/fv348MMP6dWrF5CfKN61axcVK1bkzJkzTJ48GXNzcxwcHJS43NxcQkJCqFixIh06dCAnJ0dpW7NmjXJgYUlSU1MZM2YMc+bMwc3NDR8fH0aPHq0kqsslMw3SEl/uykwtcuioqChcXV2xsrLC39+/TPMMCQnBwcEBOzs7Nm/erNUWGBhI5cqVqVWrFkeOHCky/syZM9SqVav0dQshhBBCCCGEEEKIFybJZfE/y9jYGG9vb60SE2Xx66+/0qtXLyIjIzExMVEO2iuJRqNhzJgx1KpVixkzZjBlyhTmzZuHRqNh4sSJAPz555/cuXMHjUbDiRMnlNi2bdsC8P3333Pnzh0+/vhjnjx5wqNHj3jy5AlPnjwhJSWF+/fvKzE5OTn07NmTR48ecejQIbKzs19ojUlJSXh7e9OwYUOGDRsGwMKFC7l69Spjx44tsS51ieIi4cqJl7tuXcDIwICK5pbKsGq1Gm9vb5o2bcr58+eJjo5mw4YNJU4lKiqK/v37M336dPbv38+MGTO4du0aAPv372fq1KmsWbOGTZs24evry+PHj7Xis7OzGTlyZPk/CyGEEEIIIYQQQghRIjnhSvx/obhdrs8nDtPS0tixYwfz5s1j2rRp9O3bF8jf5ftsWYVndwoDfPbZZ/zyyy9cuHABAD8/Px4+fIi3tzeJiYmcPXuWr7/+mvbt2zN27Fhmz57N/fv3uX//PoMGDWLjxo1cvXoVJycnPvjgA7y9vXFxccHOzg5dXV3UajUJCQk8fvwYZ2dnjI2NlXIdb7/9NufOnSu0NrVaTVZWVqGSD7t378bPzw8HBwetOsumpqb8/PPPtG7dmhs3brB+/Xrs7OzK+AnnOz57CWbmZi8UU5SK5pbUsK2k3O/du5ekpCSWLFmCiYkJAQEBjB07lqFDhxY7xtq1a2nbti2+vr4AjBs3jo0bNzJ37lxWrVrF4MGD6datGwDdunVjx44dSl+AL7/8UhLLQgghhBBCCCGEEK+R7FwW/9MOHjzI4MGDUavVWFlZKc+vXbvGjBkz2L9/v1b93s2bN1O5cmXi4uL49ddf8fPzY/To0WzZsoXOnTuTlpZG9+7dOXr0KI6OjkrcyJEj2bFjh5KMNTMz49SpU6hUKvbv34+5uTnTp09n6NChTJ06lQkTJmBgYMDKlSvp2bMnAwYMYO7cuVy6dAkHBwcCAwN55513sLS0REdHByMjI+zt7Vm2bBkAU6ZMYcWKFQD88MMPPHnyRJlLUFAQH330EZUqVcLOzo5q1aoB+aU02rdvT9euXenevTsHDhzA0NCQzMxMJfaNN97g5MmT3L9/HycnJ2JiYl79N6UUzyeWASIjI3F3d8fExASAhg0bEh0dXeI4kZGRtGvXTrl3c3MjLCys1DaAmJgYvv76a+UzFkIIIYQQQgghhBCvnkrzUgVahXi9oqKiWLNmDV27dqVDhw7K8/T0dHr37k3z5s2ZOHEipqamStv169d58803+fPPP7G3tyc7Oxt9fX2lPTg4GCcnJxo3blyuOT158gRra2vlPi8vr9TSHbm5uahUqkL9NBoNdnZ2zJo1i5EjRwLQoUMHevbsia2tLaNGjeLSpUtUrVqVffv2MXr0aFJSUjA1NeX+/fu8+eabuLu7s3TpUry8vBg7diy//vor69atY9++fcrO3tIkJydjaWkJXduA/sv9QYORgQHXlq3XSjBPmTKFzMxMAgMDlWe2trbExMRo/dLgWU2bNuXjjz9WallfvnyZfv36ERkZiY2NDfv27cPV1RXIL4WyZs0afv75ZyC/VEnXrl15//33adOmDbGxsS+1JiGEEEIIIYQQQoh/k4JcUVJSEhYWFsX2k7IY4n9agwYNWL58eaHnJiYm7N69u8iYN998EwB7e3sArcQyQJ8+fV5qTs8mloEy1YTW1dUt8vnevXvJyclhyJAhWn0rVqyIj48PR48eZc2aNXzxxRd07NiR2NhY5s6dS/Xq1Zk5c6ay+3fHjh2kpqayZ88erl69yuLFi6lfv/6LL87BGSxtSu9XnMxUMm9d4FFKklZyWU9PD0NDQ62uRkZGpKenF5tcfj6moH9pbevWrSMjI4MJEyZw+/bt8q9FCCGEEEIIIYQQQpRIkstC/I0WL16Mh4eHVj1oyE+eAnz11VeFkrJFCQoKokmTJiQlJZGdnU1iYiIZGRkvPiEjUzCt8OJxpbC2tiYqKkrrWUpKSqF1Px+TkJBQZP/i2h4+fMjnn3/OoUOHXvggSCGEEEIIIYQQQgjxYiS5LMTf5MiRIxw9epQPPviA7t27c+HCBXR0dHjw4AHh4eFMnDgRyC+d4eTkxH/+8x8aNGiAmZkZ+vr6PHz4EHt7e7y8vHjy5Am7d+9m165d7N69m0WLFv29i3uOq6srQUFByv2tW7dQq9WFdoE/H3P27FmGDx8OQHh4uFJ/uqCtffv2Wm179+4lISGBli1bAvklS1JTU6lQoQIXL16kRo0ar2uJQgghhBBCCCGEEP86srVPiL+BWq3Gz8+PVq1aAbB161ZiY2OJjY3F0dGRrVu3EhcXx9WrV4mNjWX37t3o6+vTuHFjBg0axNKlS7Gzs2P+/PlYWVlx/PhxrZ26Go2GjIwM8vLyin1/cnKy1vU6tW7dmuTkZNavXw9AQEAAHTp0QFdXl8TERHJzcwvF+Pj4EBwczKVLl0hNTWX58uV4enoC0LNnT1auXEl8fDwPHjxg3bp1eHp64uPjw/Xr14mIiCAiIoI9e/ZgZ2dHRESEclijEEIIIYQQQgghhHg1ZOeyEH+DzZs3Y29vzwcffMC+ffuUcg+5ubncvHlTa4etSqXCwMBASR7fv3+fypUrK+3379/njTfeUEppADg6OqJWqzl16pRSg/pZ8+fPZ9asWa9reYXo6emxdu1a+vbti7+/Pzo6Ohw7dgwAKysrwsPDadSokVaMs7MzEyZMwMXFBSMjI2rXrs2YMWMA8Pb2Ztu2bdSuXRuA9u3b06NHD1QqFWZmZoXe7ejo+LqXKIQQQgghhBBCCPGvo9JoNJq/exJC/Nvk5eUppSz27dtHcHAwANHR0TRu3JiUlBQMDQ3JyMjAyMgIgHv37tGrVy8ePXrEmTNncHR0xM/PDz09PWbOnPlC71er1ajVauU+OTk5/wBE/0/Bukr5F5aWCFdOELZwJU1q1S7UfP/+fcLCwnB3d8fGpmwHB0ZHRxMfH19kberQ0FDS0tLw8PBApVKVf95CCCGEEEIIIYQQQpGcnIylpSVJSUlYWFgU20/KYgjxN9DR0aFixYqFnu/cuZN33nmnyIPuVCoVcXFx1KtXD2trawICAjh8+DAAP/zwAyYmJjg6OuLo6IiZmRmrV68u9v2GhoZYWFhoXX+FKlWq4OXlVebEMkC9evV49913i/xMXF1dadOmjSSWhRBCCCGEEEIIIf4GklwW4n9Ebm4uGzdupEuXLoXaNBoNGo0GfX19Wrduzddff01OTg5vvvkmGo0GIyMj2rVrp9Rt7tmzZ/kmkZmWv/u4vFdmapHDRkVF4erqipWVFf7+/pTlDyZCQkJwcHDAzs6OzZs3a7UFBgZSuXJlatWqxZEjR4qMP3PmDLVq1SrDooUQQgghhBBCCCFEeUjNZSH+R6xYsYKEhASGDx9eqK1Vq1bMmzcPU1NTrdrECQkJ5OXloaOjw9OnTzl16hQADx8+LN8k4iJB/+V+LBgZGFDR3FK5V6vVeHt74+npSXBwMH5+fmzYsIGhQ4cWO0ZUVBT9+/cnMDCQZs2a0aNHD5o0aYKTkxP79+9n6tSpBAcHY2try4ABAwgNDdXaDZ2dnc3IkSOLPdBQCCGEEEIIIYQQQrw8SS4L8RpoNBoeP35MfHw8N27c4NKlS9y/f59Vq1Zp9cvLyyMvL49du3bx0UcfsXDhQqVEhampKV9++SVqtZrz589Tq1Ytbt68ybhx4wB48uQJubm5DBs2jJycHC5dusSqVaswNjbm+vXr5Zr38dlLMDM3K71jCSqaW1LDtpJyv3fvXpKSkliyZAkmJiYEBAQwduzYEpPLa9eupW3btvj6+gIwbtw4Nm7cyNy5c1m1ahWDBw+mW7duAHTr1o0dO3YofQG+/PJLSSwLIYQQQgghhBBCvGaSXBbiJe3fv5+xY8cCoKuri6GhIWlpaVSvXp2KFStSsWJFEhISeOedd0hISMDW1pb09HT09fXJysoiOzubGzdukJ2dTcOGDZVxN27cyIkTJ1CpVOzcuZOcnBxatGjBwYMHAejcuTM1a9YkKytLOaBv7ty51KxZk0mTJikHAb6IRjXfeOX1lyMjI3F3d8fExASAhg0bEh0dXWpMp06dlHs3Nzdmz56ttPXr10+r7cSJE0pyOSYmhq+//ppt27YxbNiwV7oWIYQQQgghhBBCCPFfklwW4iW9++67BAcHM27cOI4ePUpubi5vvfUW69at48033yQnJwcHBwf69OmDra0tAK1bt+bevXvo6+sDcPbsWTQaDUOGDFHG1Wg0ZGVl4efnR8eOHTl37hynT5/GxsYGlUpFcnIyRkZGGBgY8N1335GdnU3Tpk3R0dFBrVZTrVo1rfHKIuLWjZfaufz8rmXIP120Zs2ayr1KpUJXV5enT59iZWVV5DjPx1hYWHD37t1S2wBGjRrF559/LvWWhRBCCCGEEEIIIV4zSS4L8ZJ0dHRwcXGhevXqfPPNN0ybNo2JEycyf/581q1bR1BQEE2bNqV3795KzPnz55WvHzx4wKBBgzh16hS9evXinXfeoXXr1oUSr82aNSM9PV2579ixI76+vsrhfVWqVOHUqVO8+eab5V6Lx4zJL1Vz2cjAgGvL1mslmPX09DA0NNTuZ2REenp6scnl52MK+pfWtm7dOjIyMpgwYQK3b98u9zqEEEIIIYQQQgghROkkuSzES/Lx8SE+Pp6kpCTi4uL46aefyMrKIjc3F3d3dy5fvoy1tTUNGjTg7bffZvPmzfz2228cPHiQ3377jRMnTuDj40NoaCjnz59n8+bNDBkyhPr16zNx4kQlefy8nj178tZbbyn3n3/+ebHJ2jJzcAZLm9L7FSUzlcxbF3iUkqSVXLa2tiYqKkqra0pKCgYGBsUOZW1tTUJCQpH9i2t7+PAhn3/+OYcOHUJHR6d8axBCCCGEEEIIIYQQZSbJZSFeUlRUFP/5z39o06YNANu2beP27dtMmTJFq9++ffuYO3cumZmZZGZmcuLECby9vQkKCsLOzg6AevXqMWjQIDIyMggODuaNN94gPT0dPT09DAwMyM3NRa1WY2hoqHWAHaAc9PdSjEzBtMLLj/MMV1dXgoKClPtbt26hVquxtrYuMebs2bMMHz4cgPDwcKpVq6bV1r59e622vXv3kpCQQMuWLYH8wxJTU1OpUKECFy9epEaNGq90XUIIIYQQQgghhBD/diqNRqP5uychxP/PCkpR2Nraoquri6+vL2+++SYff/yx0icvL4/Hjx/z6NEjVq1aRUhISIk7dwHi4uKoXr06Go2GH3/8kdatW3PmzBl69OiBvr4+urq6Wv3j4+PJyclBV1eXyMhI6tevX+zYBQcAFkhOTsbe3h78PwXrKuX7INIS4coJwhaupEmt2srjnJwc7OzsWLBgAUOHDmXEiBHcv3+fX375hcTERMzNzQutJTIykpYtW3L27Flq1qxJq1atGDBgAFOmTGHXrl2MHj2a0NBQ9PT0aNq0KcuWLcPT05NHjx4pY9y5c4c+ffpw6tQpqlevjp6e/C5NCCGEEEIIIYQQoiySk5OxtLQkKSkJCwuLYvtJclmIV6B79+5cvXoVtVrNnTt3cHJy0mrPzs6mVq1a7N27t8xj6unpcefOHapUKTnZGxcXx6RJk7hw4QIff/wxffr0oUKFCiXGzJw5k1mzZhVueA3JZYBdu3bRt29fjI2N0dHR4dixY9SrVw+VSkV4eDiNGjUqNNxnn33G4sWLMTIyonbt2pw8eRJjY2M0Gg2DBg1i+/btALRv355du3ahUqm04mNjY2nTpg2xsbHlW48QQgghhBBCCCHEv5Qkl4X4i+Xm5tKpUyfat2/PRx99VGr/L7/8krlz51KxYkXlWVxcHFevXsXJyanU5HJmZiYLFy4kMDCQiRMnMnny5EIH5xXnr9y5XOD+/fuEhYXh7u6OjU3Z6jpHR0cTHx+Ph4dHoZ3eoaGhpKWl4eHhUSixLIQQQgghhBBCCCHKr6zJZfk7cSFegYyMDPr160d4eDi//fYb27ZtU9piYmJ499132bZtm9ZBc2ZmZvTs2ZMNGzYoz4yMjEotlwFw/Phxhg8fTqNGjYiMjCx1d/PzDA0Ny5yIflWqVKmCl5fXC8XUq1ePevXqFdnm6ur6KqYlhBBCCCGEEEIIIcpJp/QuQoiSHDx4EBcXFxo1asSff/6Jl5cXPXr04OTJk7z//vu0b9+eH374QSuxXCAkJARHR0flenY3cXG++eYbevTowaxZswgJCSkysfzll18SFhb24ovJTMvfgVyeKzO1yCGjoqJwdXXFysoKf39/yvLHEiEhITg4OGBnZ8fmzZu12gIDA6lcuTK1atXiyJEjRcafOXOGWrVqlWXFQgghhBBCCCGEEKKcZOeyEC/h9u3brF27lk2bNtG4cWMyMzOZPHkygwcPZt68eVSvXp2lS5dy48YNjI2NMTMzo1KlSgCkpqYWuXM5KyuLrKysIpOwT58+ZeLEiQQFBdG7d+8i55SQkMD8+fOxtLSkadOmL7aguEjQL/+PBSMDAyqaWyr3arUab29vPD09CQ4Oxs/Pjw0bNjB06NBix4iKiqJ///4EBgbSrFkzevToQZMmTXBycmL//v1MnTqV4OBgbG1tGTBgAKGhoVplNrKzsxk5ciR5eXnlXocQQgghhBBCCCGEKJ3UXBbiFViwYAHLly/H1NQUd3d3vL29admyJQcOHODo0aNERERw69YtZsyYwdSpUwE4cOAAT58+5YMPPlDG2bFjB46Ojnh5eZGens7Dhw+1ymTk5ubSv39/Tpw4QUZGRpEJaAMDA5o2bcrWrVsxNzcv0/wL6ugcj7iAmblZuT+HiuaW1LCtpNzv3LmTYcOGcefOHUxMTIiMjGTs2LGcOnWq2DEmTpzI1atX2bdvHwDLli0jISGBuXPn0r17d6pUqcLq1asBmDRpEvXr18fX11eJnzNnDps3byY9PV0O8xNCCCGEEEIIIYQoB6m5LMRL+Pnnnzlz5gwLFizQev748WNu3brFqVOnyM7Oxt/fH4Bx48Yxbtw4TE1Nlb7Tpk2jadOmfPfdd0W+47333iM3N1fr2fvvvw9AQEAATZs2RV9fX6tdV1eX4ODgUuefk5ODnt6L/+/dqOYbJf7AeFGRkZG4u7tjYmICQMOGDYmOji41plOnTsq9m5sbs2fPVtr69eun1XbixAkluRwTE8PXX3/Ntm3bGDZs2CtbhxBCCCGEEEIIIYQoTJLLQjwjLS0NY2NjcnJy2LVrFwEBAajVagwNDXFzc+PChQuYmZlRo0YNatSowahRo1i+fDnnzp0jKChIK7ncqFEjZs6cSc+ePdHV1S30rqysLFq1akVQUBB2dnZs2bKFzMxMhg0bxsCBA5kwYQKVK1dm+vTpWnHfffcdhw4dYuPGjajVavT09NDV1WXgwIG4uroyYMAAhg0bxsaNGzExMSny3cWJuHWj3DuXn9+1DPm/5apZs6Zyr1Kp0NXV5enTp1hZWRU5zvMxFhYW3L17t9Q2gFGjRvH5559LvWUhhBBCCCGEEEKIv4Akl4V4hqWlJXl5ecrhe4aGhuTm5nL06FFUKhW//PILXbp00YoZOHAgu3bt4u233yYiIoJWrVop9X4zMjJ44403AGjRogU//vgjkL+zePDgwbRo0QILCwvatGnDxIkTyc3NpW/fvnz77bfExMTQv3//QnPU09NDpVIB8M477xAfH4+BgQGPHj1iz549LFmyBIC6desyffp0Ro0aVeb1e8yYXO6ay0YGBlxbtl4rwaynp4ehoaF2PyMj0tPTi00uPx9T0L+0tnXr1pGRkcGECRO4fft2udYghBBCCCGEEEIIIcpOkstCPCM1NZXPPvuMRYsWoaOjw5AhQ/jiiy9wdHRER0cHM7PCu3odHBw4evQoa9eupVq1asTHxxMfH0/FihWVPhs2bGDLli3K/eHDh8nOzmbSpEncuXMHQ0NDdHR00NHRUb4+d+4cR44c4fTp0+jr6zNhwgQgvzRGQfL71KlTZGRkADBmzBhcXV2Vw/IMDQ0xNjZ+sQ/AwRksbUrv97zMVDJvXeBRSpJWctna2pqoqCitrikpKVp1pJ9nbW1NQkJCkf2La3v48CGff/45hw4dUj4bIYQQQgghhBBCCPF6SXJZiP+Tk5MDwNOnT4mKiiI9PZ2rV69iZ2dHdnY2Ojo6HDlyhPv37yv9PTw8sLe3x9TUVEn+Pl8nucCz5Sk8PT3x9PTks88+4/bt2zx48ICvvvqKvLw8MjIyOHLkCPXr18fJyYnx48ezatUqANRqtXKIX0ZGBkFBQUydOhUTExPS09PZuXMns2bNQq1WM2bMGL766qsX+xCMTMG0wovFlMDV1ZWgoCDl/tatW6jVaqytrUuMOXv2LMOHDwcgPDycatWqabW1b99eq23v3r0kJCTQsmVLAPLy8khNTaVChQpcvHiRGjVqvLI1CSGEEEIIIYQQQoh8ssVPiP+zb98+jI2N+e6772jcuDEtWrTg999/x8jIiIULF6LRaPjjjz84d+4cffv2JTQ0lJ9//pkmTZqwefNmpRQGQJMmTXB0dFSuqVOnFnrf3bt3CQ4OJjAwkLi4OC5fvkx0dDQxMTGcO3eOESNG8P7771OhQgW6d++ujDts2DB+/PFHrKysyMvLo3nz5qxevZrmzZvTr18/Vq9ejY+PT4m7ltVqNcnJyVrX69C6dWuSk5NZv349kH9QYYcOHdDV1SUxMbHQgYYAPj4+BAcHc+nSJVJTU1m+fDmenp4A9OzZk5UrVxIfH8+DBw9Yt24dnp6e+Pj4cP36dSIiIoiIiGDPnj3Y2dkRERGBnZ3da1mbEEIIIYQQQgghxL+d7FwW4v907tyZvLw8VCoVISEhbNiwgd27d6PRaMjLy+Onn35i8uTJvP3223z99dcsW7YMtVqNiYkJ06dP59q1a8ycOROACxcuFCqLsXXrVq33jRo1Cnt7e06ePMn8+fPR09MjLy8PR0dHdu/eTWZmJl5eXpibmysxly9fJjg4mH379rFhwwZWr15Nbm4umZmZ5Obmkp2dTWZmprILuzjz589n1qxZr+7DK4aenh5r166lb9+++Pv7o6Ojw7FjxwCwsrIiPDycRo0aacU4OzszYcIEXFxcMDIyonbt2owZMwYAb29vtm3bRu3atQFo3749PXr0QKVSFSpZoqenh6Oj4+teohBCCCGEEEIIIcS/liSXhfg/Ojo6PH78GH19fSVZm5KSQk5ODsbGxqSlpWFqaqoVY2hoyLBhwxg4cKDW8yZNmpCenk5WVhbW1tZoNBqaN2+utK9evZq7d+9ibm6Ol5cXXl5eStvjx49xdXVl+/bt3LlzB1tb22LnrNFouHz5MosXLyY+Pp6bN28SFhbG48ePcXBwKDbuk08+YfLkycp9cnIy9vb2Zf6sXkTXrl25ceMGYWFhuLu7Y2Njo8y9OPPmzaN///7Ex8fj4eGh1FxWqVRs3LgRPz8/0tLS8PDwUA43fJajoyOxsbGvZT1CCCGEEEIIIYQQIp+UxRDi/+Tk5FClShWqVavGqFGjOHToENWqVcPOzo7g4GDu3r1L1apVi4y9cuUKv/76q3J/4cIFdu/eTdWqVYmNjSUmJoZmzZqRnp4OQJs2bfjmm2+U/m3atMHZ2RlbW1tu3brF+PHjiY+P58KFC7i4uBQ7Z1tbW/z9/YmKimLUqFEsXryY8PBwNBoNo0aNKjbO0NAQCwsLret1qlKlCl5eXkpiuSzq1avHu+++W+Thf66urrRp00ZJLF++fLnQwYFCCCGEEEIIIYQQ4vWS5LIQ/0dPT4+nT58yYsQIpc7vqlWriI2NpXnz5lhbW2NlZVVk7KxZs/j555+1nrm7u2NgYKCMtWfPHhISEgB46623tA6ZS0xMZM+ePXh6eqKrq4taraZx48YEBATQo0ePIt+5fft2fH19WbhwIRUqVGD16tWMGTMGW1tbHjx4QJMmTbC0tEStVpf9Q8hMg7TEF78yU7WGiYqKwtXVFSsrK/z9/UvcpVwgJCQEBwcH7Ozs2Lx5s1ZbYGAglStXplatWhw5ckR5np6eTqtWrejSpQvvvvsuLVu2JDMzs+zrFUIIIYQQQgghhBDlJmUxhPg/Go2G0aNHo9FocHd3B/JLVPTq1Ytu3brRtGnTIuN+/fVXjh8/TkxMjNbzb7/9lhUrVtChQwd8fHzYvHlzkSUc0tPTuXnzJlWqVCE3N5dhw4Yxb948zM3NefLkCXXq1CnyvV5eXty/f5/Tp09z6tQpvvjiC6VNT0+PJ0+ekJGRgaGhYdk/hLhI0C/fjwUjAwMqmucns729vfH09CQ4OBg/Pz82bNjA0KFDi42Nioqif//+BAYG0qxZM3r06EGTJk1wcnJi//79TJ06leDgYGxtbRkwYAChoaHY2NiwcOFCqlevzokTJ8jMzKRp06YEBwczZMiQcq1BCCGEEEIIIYQQQpSdJJeF+D9nz54lIyOD1atXs3nzZnR0dBg/fjwNGzZk7NixfP755wDk5eUp/42Pj2fYsGFMnz4da2trAHJzcxkyZAhhYWGcPn2adevWMXr0aIYPH46vry/u7u7o6OiQl5dHXl4eixYtwtvbG11dXSpUqMCnn37Kli1buHfvHqNGjaJt27asWLGiUHkMIyMjAGrWrEmPHj3o27cvderUITMzE5VKhY6OTqEa0aU5PnsJZuZmpXcsQkVzS2rYVmLnzp0kJSWxZMkSTExMCAgIYOzYsSUml9euXUvbtm3x9fUFYNy4cWzcuJG5c+eyatUqBg8eTLdu3QDo1q0bO3bswNfXl7feeoshQ4agUqkwNjbmrbfe4vHjx+WavxBCCCGEEEIIIYR4MZJcFuL/tGjRghYtWrBlyxaCgoKYMWMGKpUKExMTdHR06NmzJ4BSZiIrK4s7d+5QvXp1Ro8eDcCNGzdQq9Xo6elx8eJFbG1tqVWrFg0bNsTf359Ro0YRGhqKkZERGRkZZGZmMmjQIGV38cyZM/Hw8KBXr16sW7cOPT09goKC+O6775Tkslqt1ip1UatWLa5evUrVqlXZt28fQ4YMwdnZuVyfQaOab7x0/eXIyEjc3d0xMTEBoGHDhkRHR5ca06lTJ+Xezc2N2bNnK239+vXTajtx4gS+vr706dNHeR4REcHRo0eZP3/+S81fCCGEEEIIIYQQQpSNSlOWYqhCiGLl5eWho/Pf8uVhYWHFltBISUnB3Ny80PPz58/TpEkTdHR0yMnJQU+vbL/3+f3333Fzc1PuMzMziYyMpEmTJujr65d5DcnJyVhaWnI84sIL71wu2LFcYMqUKWRmZhIYGKg8s7W1JSYmptia1U2bNuXjjz+mV69eQP4Bff369SMyMhIbGxv27duHq6srkF+GZM2aNVo1rocOHcr333/PvHnz+Pjjj19o/kIIIYQQQgghhBBCW0GuKCkpqcSNiLJzWYiXpKOjw4QJEzAwMGDRokU0bdqUNWvWkJqayuTJk4H8HcmPHz/mm2++KRR/8uRJ+vXrx9GjR3nzzTfLnFjeunUrn332Gb/99hs2NjZAfqmMZs2alXstHjMmv3DNZSMDA64tW68kmPX09ArVeTYyMiI9Pb3Y5PLzMQX9S2srsGTJElxdXZk2bRrvvfceTZo0eaE1CCGEEEIIIYQQQogXJ8llIV4BAwMDpQYyQKtWrWjZsiV9+/bFxsaGoKAgVq1aVShu586djB49mgoVKtC9e3fl+YMHD3B0dOTUqVNFHsi3evVqpk+fTsWKFfHw8FCex8fH06pVK37++eciDw8slYMzWNqUvX9mKpm3LvAoJUlJLltbWxMVFaXVLSUlBQMDg2KHsba2JiEhocj+JbUVsLKyYsyYMZw7d46NGzdKclkIIYQQQgghhBDiL6BTehchRHFyc3PJyspCR0cHHR0d1Go1Dx48ICoqiiVLlnDu3Dk++eQTpe/WrVvRaDTcu3ePkSNHMmvWLEJCQvjPf/5DVFQUUVFRBAUFYWxszA8//FAosXz9+nV69OjBtm3b2LZtG8HBwUrcnDlzsLW1Zd26deVLLAMYmYJphbJfRoVLaLi6unL27Fnl/tatW6jVauXAw6I8HxMeHk61atVKbRs4cCDXrl1T2gwMDNDV1X3BRQshhBBCCCGEEEKI8pDkshAv4ciRIzRs2JBvv/2WlStXUr9+fR4+fEh4eDgff/wxe/bswdzcnNzcXPbs2UNERAQajYaIiAgqVKjAb7/9hkqlwsfHhxMnThAcHEzfvn0JCQmhTp06hd534sQJ3N3dOXjwII8ePeK9994jOjqaZcuW8dFHH7F3715sbW1LnbdarSY5OVnrelVat25NcnIy69evByAgIIAOHTqgq6tLYmIiubm5hWJ8fHwIDg7m0qVLpKamsnz5cjw9PQHo2bMnK1euJD4+ngcPHrBu3TqlrXLlygwZMoQrV65w7NgxQkJC8PHxeWVrEUIIIYQQQgghhBDFkwP9hHgFPv74Y4yMjJg5c6byrFGjRqxduxYXFxetr4uyePFiPv/8c95++20mT55M3759y/TecePGsXbtWpo2bUpAQIBWiYySzJw5k1mzZhVu8P8UrKuUaQwA0hLhygnCFq6kSa3ayuNdu3bRt29fjI2N0dHR4dixY9SrVw+VSkV4eDiNGjUqNNRnn33G4sWLMTIyonbt2pw8eRJjY2M0Gg2DBg1i+/btALRv355du3ahUqnIyMhg7NixbN++HVtbW+bMmVPmz04IIYQQQgghhBBCFK2sB/pJclmIV+Djjz8mIyMDFxcXBg4cCJScXI6Li+PKlSucOXOGX3/9FX19ffz8/AgODiYzM5O9e/cWWd7hjz/+4MqVK5w8eZLdu3djb2/P6NGjWbBgAfXr1+fbb78t03zVajVqtVq5T05Oxt7e/pUllwHu379PWFgY7u7uyoGDpYmOjiY+Ph4PD49CdZVDQ0NJS0vDw8Oj/GU/hBBCCCGEEEIIIUSpJLksxF/gwoUL7Nq1i59++gkjIyOGDBnCoUOHuHLlCrGxsVSrVg0jIyNu3LhB1apV0dHRYd68eTx8+JCtW7fSuXNnevTogbm5Ob179yY2NpYKFSoo49+4cYMvvviCjz/+GICPPvqI8PBwJS49PZ3333+fzMxMTE1NAdBoNMTExPD999+XeRdvwQ+MV5lc/itcvnwZjUZDgwYN/vJ3CyGEEEIIIYQQQvxTlTW5LDWXhXgJurq6ZGVl4ebmRufOnRkzZgw//fQTV65cwcbGhn379hEVFYWTkxNbt27l+vXrfPDBB4wfP56TJ08yceJE9u7dy9tvv02LFi24fPmyckDfggULsLS05MMPP1Tet2DBAg4cOMDQoUNZu3YtLVq0oH///vzxxx9K3JgxY3BycqJ3794vvqDMtPyEcVmvzFSt8KioKFxdXbGyssLf35+y/O4qJCQEBwcH7Ozs2Lx5s1ZbYGAglStXplatWhw5ckR5np6eTqtWrejSpQvvvvsuLVu2JDMz88XXK4QQQgghhBBCCCHKTZLLQrwEZ2dnAgICqFixotbz+/fvk5ycTI0aNYqNPXfuHNWrV+fYsWOcOnUKGxsbunXrRkZGBrdu3WLUqFFs2LAhf0fxM3bs2EGNGjW4ffs2Fy9eJD4+noEDB5KXl0dYWBhffPEFP/74Y5FlNUoVFwlXTpT9unUBIwMDKppbolar8fb2pmnTppw/f57o6Gg2bNhQ4uuioqLo378/06dPZ//+/cyYMYNr164BsH//fqZOncqaNWvYtGkTvr6+PH78GICFCxdSvXp1bt68yc2bN3n69CnBwcEvvl4hhBBCCCGEEEIIUW56f/cEhPgnmjNnDj4+PoXqBj+rWbNm/P7777zxxhsAODk5cfXqVd577z1u3brFl19+SceOHQvFdenShUuXLimJ66VLl9KtWzc6derExYsX2bJlCw0bNizXvI/PXoKZudkLxVQ0t6SGbSV27txJUlISS5YswcTEhICAAMaOHcvQoUOLjV27di1t27bF19cXyD+gcOPGjcydO5dVq1YxePBgunXrBkC3bt3YsWMHvr6+vPXWWwwZMgSVSoWxsTFvvfWWkngWQgghhBBCCCGEEH8NSS4L8ZJ++uknTp8+TefOnYH80hXBwcFcvnxZ6ZObm0tubm6h2DfeeAONRsOlS5fYv38/v//+O6ampvz88880bdq0yPfp6+tTo0YNcnJyuHDhAnv27CEmJoY6depw8uRJ3nzzzXKvpVHNN0qso1OSyMhI3N3dMTExAaBhw4ZER0eXGtOpUyfl3s3NjdmzZytt/fr102o7ceIEvr6+9OnTR3keERHB0aNHmT9/frnmLYQQQgghhBBCCCHKR5LLQrwC7733HqNHj+bChQts376dw4cPU6XKfw/Gy8jI0KoJvGnTJrZs2UJ8fDw3btzAwsICLy8vVq9eTfPmzYt9z5IlSzh8+DB//vknN27cwM7ODm9vb3bs2EGjRo1eeh0Rt26UeedywY7lAsnJydSsWVO5V6lU6Orq8vTpU6ysrIoc4/kYCwsL7t69W2pbgaFDh/L9998zb948nJycyjRvIYQQQgghhBBCCPFqSHJZiJfUo0cPevToAYCVlRW///57oT7Xr1/Xuu/QoQMpKSmcO3cOFxcX1qxZo7SFhISwZMkSzpw5U2gcLy8vzMzMcHBwoHbt2hgYGPDkyRMePHjAhg0biImJ4ffff6dXr16MGjXqhdfiMWMy6Jftx4KRgQHXlq1XEsx6enoYGhpq9zEyIj09vdjk8vMxBf1LayuwZMkSXF1dmTZtGu+99x5NmjQp09yFEEIIIYQQQgghxMuT5LIQf4MqVarw4YcfkpqaWqhWsIGBAba2tkXGWVtbM3HiRHJzczE3N8fCwoLU1FSMjIxo164dVapUoUuXLiUeJFgiB2ewtCm9X2Yqmbcu8CglSUkuW1tbExUVpdUtJSWlxLrT1tbWJCQkFNm/pLYCVlZWjBkzhnPnzrFx40ZJLgshhBBCCCGEEEL8hSS5LMTfJCQkhPT0dO7evcv48eMxNTUlODgYjUZDYmIijRo1IisrC09PT5YuXQqAra0tqamp6OjoKON8/vnn3Llzhw0bNrz8pIxMwbRCuUJdXV0JCgpS7m/duoVarcba2rrEmLNnzzJ8+HAAwsPDqVatmlZb+/btC7UNHDiQzz//XCmFYWBggK6ubrnmLYQQQgghhBBCCCHKR6f0LkKI12HQoEFkZ2dTtWpV9u7dy4QJE4iNjSUwMJC2bdsSERHBtGnTSE5O1orLzMwkJyen2HFzc3MLlY94nlqtJjk5Wet6Wa1btyY5OZn169cDEBAQQIcOHdDV1SUxMbHIAw19fHwIDg7m0qVLpKamsnz5cjw9PQHo2bMnK1euJD4+ngcPHrBu3TqlrXLlygwZMoQrV65w7NgxQkJC8PHxeek1CCGEEEIIIYQQQoiyk53LQvwN7t27h6mpKRUqVODRo0d07tyZ3bt3M2LEiEJ9VSqV1n3dunVJTExEX18fgPT0dPLy8ti9ezcAOTk5WFpaEhcXV+z758+fz6xZs17hivJrJK9du5a+ffvi7++Pjo4Ox44dA/LLV4SHhxc6dNDZ2ZkJEybg4uKCkZERtWvXZsyYMQB4e3uzbds2ateuDUD79u2V2tZz5sxh7NixuLu7Y2try8qVK0s8CFEIIYQQQgghhBBCvHqSXBbibxAZGUmDBg2U+xkzZmBpaVmm2OeTxuUpi/HJJ58wefJk5T45ORl7e/syxxena9eu3Lhxg7CwMNzd3bGxya/frNFoio2ZN28e/fv3Jz4+Hg8PD6WuskqlYuPGjfj5+ZGWloaHh4eSaDc2Nubbb7/l22+/fek5CyGEEEIIIYQQQojykeSyEH8DGxsbxo0bx61btwCIj4/H2dkZExMTMjIyePLkCfXq1SM9PZ3U1FQOHDjAyZMnqVSpEkZGRoV2Mz9Po9GQmZmJoaGhVn3mAoaGhhgaGr6WtVWpUgUvL68XiqlXrx716tUrss3V1fVVTEsIIYQQQgghhBBCvGKSXBbib+Dq6oqrqyuLFy8G8stDxMfHAzBy5EiuXLmCs7MzK1asUGKOHDlC3bp1MTY21kouP18WA/KTyxkZGYSHhyuH3pVJZhqkJZahX2rZxxRCCCGEEEIIIYQQ/0hyoJ8Q/0Pu3r3Lr7/+yu7duzl//jz79+9X2tq1a0d6ejqPHz/m0aNHyjV58mT69Omj9ezx48ekp6e/WGIZIC4Srpwo/bp1ASMDAyqa/7eUR1RUFK6urlhZWeHv719iKYwCISEhODg4YGdnx+bNm7XaAgMDqVy5MrVq1eLIkSPK89TUVHr37o2JiQkWFhZ8/vnnL7ZGIYQQQgghhBBCCPFKyM5lIf5GGo1GScJmZ2czcOBApk+fjqWlJd9++y3vvfceW7ZsoWXLln/JfI7PXoKZuVmZ+lY0t6SGbSUA1Go13t7eeHp6EhwcjJ+fHxs2bGDo0KHFxkdFRdG/f38CAwNp1qwZPXr0oEmTJjg5ObF//36mTp1KcHAwtra2DBgwgNDQUGxsbJg0aRIZGRlcvnyZ2NhYOnfujIeHB+++++4r+QyEEEIIIYQQQgghRNlIclmIv1F2djY5OTncu3ePAQMG8MYbbzB69Gggvw5xUFAQXl5ezJs3jzFjxhRZazk9Pb3UGsxl1ajmG1hYWLxw3N69e0lKSmLJkiWYmJgQEBDA2LFjS0wur127lrZt2+Lr6wvAuHHj2LhxI3PnzmXVqlUMHjyYbt26AdCtWzd27NjBsGHDyM7O5ocffsDCwoKaNWvi5uZGeHi4JJeFEEIIIYQQQggh/mJSFkOIv1FOTg45OTkEBATQrFkzVq9erdXeqVMn9uzZw9atW0lISNBqi4+Pp2HDhixfvpy6deu+kvlE3LrBhZt/lHjdTnhYKC4yMhJ3d3dMTEwAaNiwIdHR0SW+KzIyknbt2in3bm5uhIWFldimo6PDhg0blAR4bm4u169fp3bt2i+9diGEEEIIIYQQQgjxYmTnshCviEajITc3l8zMTJKTk3ny5AkPHz7k7t27/PHHH4SFhdGkSRNmz56txNSoUYOdO3dy4cKFYsdt0aIFx48fL/S8WrVq+Pv74+joyDvvvPNK1uAxYzLol/xjwcjAgGvL1islMQCSk5OpWbOmcq9SqdDV1eXp06dYWVkVOc7zMRYWFty9e7fUtmd9//336Or+P/buPK6qan/8/+twDqMMMqgoKqDilIoDGDnhPIaYYmlqTpRjmoY5m5ZilprziGmiaUWOpZJec8xSUREktRQccAgUOIyH4ZzfH1z25cgglJm/z/f9fDz247L3Wu+119pe/ePN6r3U9OzZs2wLFEIIIYQQQgghhBDPjOxcFuIZyM7Opnr16lhZWeHq6krr1q3p1q0br7/+OuHh4WRkZNChQwcaNWpkFGdpaYmNjY1yv23bNkxNTalYsSI2NjZUqlSpyLvWrVuHi4sL1tbW/PTTT7Rs2VIpizF37lycnJywt7dn6tSpZTpUz4irJzRoV/Ll3pys7GwSU1OMwjQaDebm5kbPLCwsyMjIKPFVT8YU7l9aW4H79+8TFBTEkiVLirxbCCGEEEIIIYQQQvzzZOeyEM+AmZkZt2/fRq1WK89CQkLYtm0boaGhRfrn5eWh1+tRq9WoVCoMBgM5OTlYWFjQo0cP9u3bx/nz53nttdeM4o4fP86kSZMIDQ2lXr16BAQE8PHHHzN//ny2bt3KypUrCQsLw9zcnD59+uDh4aHUNC4TiwpQoWK51+/g4EB0dLTRs9TUVMzMzEqNKVzqo3D/0toA9Ho9Q4YMwc/Pj/79+5d7vkIIIYQQQgghhBDi75Ody0I8I9nZ2eTk5JTYrtfrSU9PB2DXrl04OzsTGBjIL7/8Qs2aNRk0aJCSbC5QOFkN+WUg+vfvT0BAAI0bN2bmzJls374dgC+//JJx48bRoUMHWrVqxfjx45W2J+l0OrRardH1d3h7e3PmzBnlPjY2Fp1Oh4ODQ5ljLl68iIuLy1PbAKZNm8aff/7JmjVr/ta8hRBCCCGEEEIIIcRfJ8llIZ6Rbt264ejoiJOTE05OTkyaNInTp08r946Ojjg6OqLT6ejfvz+PHj2iY8eO+Pj4cOfOHb799lsMBkORhHJhUVFRNG3aVLlv1KgRcXFxZGRkFNtW0qF6CxcuxM7OTrlq1Kjxt9berl07tFotmzdvBiA4OJjOnTujVqtJTk4mLy+vSEy/fv3YuXMnUVFRpKWlsWLFCrp16wZAQEAAa9asIT4+nocPH7Jp0yalbevWraxfv57Q0FD0ej1paWnodLq/NX8hhBBCCCGEEEIIUX6SXBbiGTlx4gRarZbExEQSExP5/PPPad26tXKflJREVlaWUh84IyODI0eOkJWVpewwzsnJKbWURFJSEnZ2dsp9wc/JycnFtiUlJRU7zvTp00lJSVGuO3fu/K21azQaQkJCGD9+PE5OTuzdu5dFixYBYG9vT1RUVJEYT09PJk6ciJeXFy4uLqjVasaOHQuAn58fnTp1wsPDA3d3d5o1a0bfvn0B+Pzzz9FqtTRt2hQbGxtsbGwYNWrU35q/EEIIIYQQQgghhCg/qbksxN+k1+vJysrCwsICE5On/74mKysLjUZDaGgoKpWK3NxcZs+ejYmJCWlpaVSoUKHM7/0rbQDm5ubP/BC83r17c+PGDSIiIvDx8cHR0RGg1EMFFyxYwKBBg4iPj8fX11dJrKtUKkJDQ5kwYQLp6en4+voq5UIuXrz4TOcthBBCCCGEEEIIIf4aSS4L8TfFxsbSqFEjLC0tjZLLOp2OrKwsnJycjPpnZmayY8cOgoODGTJkCNHR0SxcuJD79+9z584dnJ2dS3yXo6Ojsht57NixtGjRAsjfpVy4rV+/fnTs2JGKFSs+49WWztnZmV69epUrpmHDhjRs2LDYNm9v72cxLSGEEEIIIYQQQgjxD5CyGEL8TbVr1yYzM5PHjx8rJTCKK4tRcKWnp3P58mWqVq1K+/btAejSpQtvvfUW165dKzHRCtCkSRMiIyOV+ylTpuDq6kqFChWM2jIzM5k9e3apYxUrKx3Sk0u+stKKDYuOjsbb2xt7e3umTJlS6m7lAmFhYbi6ulKtWjV27Nhh1LZ69WqqVKlCrVq1OHr0qPI8LS2N119/HSsrK2xtbZk1a1b51ieEEEIIIYQQQgghnhlJLgvxLxg1ahSbNm0yepaamsqRI0eUhHNhiYmJAAwdOpSwsDDCwsIICAggJSWFAQMGADBs2DBWr17N0aNHeeONN4zayuxWJPx2ouQr9gIWZmY42fyvtrNOp8PPz48WLVpw/vx5YmJi2LJlS6mviY6OZtCgQcyePZvw8HDmzJnDtWvXAAgPDycoKIgNGzawbds2AgMDefToEQCTJk0iMzOTK1eusHfvXpYsWcLhw4fLt0YhhBBCCCGEEEII8UxIWQwh/iEZGRlKneAnVapUiUqVKhEdHU1eXh4As2bNokuXLri4uAD5dYezs7MBaNCgAadPn6Z169asXLmSiRMnkpycjJubm5J4fvPNN7l58yavv/46ubm5uLi48Pjx43LN+fhHS7G2sS61j5ONHTUrVVbuDx48SEpKCkuXLsXKyorg4GDGjRvH8OHDSxwjJCSEDh06EBgYCMD48eMJDQ1l/vz5rF27lqFDh+Lv7w+Av78/u3fvZsSIEeTk5LB9+3ZsbW1xd3enZcuWXLx4kS5dupRrnUIIIYQQQgghhBDi75Ody0IUkpmZSVJSEunp6WRlZRV7ZWRk8PjxY3Jycood48cff8TU1JQpU6bQoEGDUt9XMGalSpU4cOAAy5YtA8DBwUEZv3HjxlSrVg0PDw/y8vIIDAxErVYTERHB999/j1arpUWLFlSpUoUWLVrQsmVL6tSpQ0pKCp07d36m3+fJxDJAZGQkPj4+WFlZAfmlO2JiYkodJzIyko4dOyr3LVu2JCIiotQ2ExMTtmzZgq2tLQB5eXn88ccfeHh4PJO1CSGEEEIIIYQQQojykZ3LQhSydetWxo0bh6mpKWq1GsSQqHUAALTTSURBVEDZPWxmZgaAXq8nOzub06dP8/LLLxfpY2dnh42NDV9//TVt27YlJyeHH3/8kR9++IHVq1ejUqlYu3Yt06dPx8bGBrVazaNHj7CwsMDHxweAlJQUAgICMDMzIzExkZdffhmVSkW/fv347LPPMDU1xdzcnNatW/PLL7/wzTffcPfuXSwtLRk4cCAvvfQSH330EZUrV35yiaXynTMZTEv+Z8HCzIxryzcbJZi1Wi3u7u7KvUqlQq1Wk5SUhL29fbHjPBlja2vLvXv3ntpW2NatW1Gr1fTs2bPsCxRCCCGEEEIIIYQQz4wkl4UoZNSoUYwaNcro2fjx43FycmLu3Lklxq1cuZJly5ahVqvJzs5Gq9Xy9ttvk5eXR8+ePQkLC2P+/PlKmYwxY8YwZswYJd7S0pKLFy/i5OQEgLOzM8ePH6d27dpG72ndujVff/01KpWKCxcu4OPjQ82aNVGpVPz+++8A1KlTh3Pnzik1jMvF1RPsHItvy0ojK/YCiakpRslljUaDubm5UVcLCwsyMjJKTC4/GVPQ/2ltBe7fv09QUBDr1q0r8m4hhBBCCCGEEEII8XxIclmIZ+D999/n/fffB+DSpUu8+uqrxMXF8c033/D+++/z9ddfl1qi4vvvv8fO7n+H5IWHhyu1lwvz9/cnKioKABMTE8aMGcNnn33GunXrsLa2Jjs7m/nz5+Pu7o6trS0Gg6F8C7GoABUqlivEwcGB6Ohoo2epqanKTu+SYhISEortX1ob5O8cHzJkCH5+fvTv379ccxVCCCGEEEIIIYQQz44kl4V4Qk5ODgaDAVNT02IP5MvOzkatVqNWq7l8+TKtW7fGxsZGSYDm5eWh1WqpWLEiubm5WFtbExgYiE6nw8bGhuvXrwPg5uZGTk4Opqampc7nzp07XLlyhfr16+Pm5kbt2rWZOnUqPj4+ODg4cO/ePYKCgmjTpg3Hjh1j6dKlNGnShIkTJ5Z4oOCz5O3tzcaNG5X72NhYdDodDg4OpcacOXOGkSNHAnDx4kUlmV7Q1qlTpyJtANOmTePPP/9k3759/8RyhBBCCCGEEEIIIUQZyYF+Qjxh9uzZmJubY2JigkqlYvXq1cybNw+VSoVKpcLc3Jxvv/0WyD+8LjU1lXv37hEXF0dcXBwhISHUrl2boKAgHj16xIMHD4iLi+P+/ftKYrnAf/7zHyUuLi6OwYMHc/r0aaNnlSpVQqPJ/z3QlClTcHR0RK/X07BhQ9zd3fHy8uKDDz4gJSWF7OxswsPDAVi+fDlubm7FrlGn06HVao2uv6pdu3ZotVo2b94MQHBwMJ07d0atVpOcnExeXl6RmH79+rFz506ioqJIS0tjxYoVdOvWDYCAgADWrFlDfHw8Dx8+ZNOmTUrb1q1bWb9+PaGhoej1etLS0tDpdH957kIIIYQQQgghhBDir5PkshBPmDVrFomJiWi1WlJTU3nnnXeYPn06qampaLVaEhMTee2114rEbdu2DVdXV7p3786tW7fYsmULL730EnXq1KFOnTpFkqCjRo3CysoKvV6vPNu1axfp6enKvU6nY+rUqVSsWBHITxj7+fmxdetW/P39+eqrr1ixYgUmJibs2bOH8+fPs3PnTt5//33GjBnDr7/+WuwaFy5ciJ2dnXLVqFHjL38vjUZDSEiIUpt67969LFq0CAB7e3uljEdhnp6eTJw4ES8vL1xcXFCr1YwdOxYAPz8/OnXqhIeHB+7u7jRr1oy+ffsC8Pnnn6PVamnatCk2NjbY2NgUqZEthBBCCCGEEEIIIZ4PKYshxBOsra2xtrZW7k1NTTEzMzN6ViA3N5cjR46wbt06jhw5QtOmTbl165ZRn6ysLCwtLYuUv6hZsyYvv/yyUn7j9u3bqFQq6tWrR7Vq1TA1NSU7O5s+ffooB/0BpKWlUaFCBQASExO5desW5ubmXLp0iaSkJO7fv09ERARZWVmsXbu22DVOnz6dyZMnK/darfZvJZh79+7NjRs3iIiIwMfHB0fH/EMBS6v5vGDBAgYNGkR8fDy+vr5KWRGVSkVoaCgTJkwgPT0dX19fpbzHxYsX//IchRBCCCGEEEIIIcSzJcllIf6GixcvMmXKFCZOnMgbb7zB8OHDi5SiKEiwmpgY/4cCgwYNYtCgQQCMGzeOe/fu8fvvv9O+fXvu3LnDt99+W+yheHfu3KFatWoAODo68s0339CyZUtmzZrFpUuXOHToEFOnTi22HEUBc3NzzM3N/87Si3B2dqZXr17limnYsCENGzYsts3b2/tZTEsIIYQQQgghhBBC/EOkLIYQf4O3tzdRUVEEBgZiamqKl5eXUb3kuLg4rl27VmL8nTt36NOnD/Hx8Xz11VcAvPfee3h4eNCqVSvOnTtn1D8zM5P4+HiqVKlCXl4eM2bMYPfu3eTk5HD16lVu375NSkoK165d4/fffy//grLSIT25+CsrrUj36OhovL29sbe3Z8qUKaXuVC4QFhaGq6sr1apVY8eOHUZtq1evpkqVKtSqVYujR48qz9PS0nj99dexsrLC1taWWbNmlX9tQgghhBBCCCGEEOKZkuSyEP+Vm5vLw4cPSU5OJi0tTblycnLIzs42epacnMzDhw+N4p+WWC28k/j27dsMHDiQFi1a0K5dO3bv3o2lpaUyxuLFi5k2bRqvvvoqbdu25eDBgwDs3r2bl19+GYPBwOnTp2nfvj1Dhw4lNTWVnTt3cvz4ce7fv8/OnTvZtGkTq1atKt9HuBUJv50o/oq9gIWZGU42dkB+PWg/Pz9atGjB+fPniYmJYcuWLaUOHx0dzaBBg5g9ezbh4eHMmTNHSb6Hh4cTFBTEhg0b2LZtG4GBgTx69AiASZMmkZmZyZUrV9i7dy9Llizh8OHD5VubEEIIIYQQQgghhHimpCyGEP917do1mjZtipmZWZH6yABr1qxRfs7JyUGlUpGW9r/dvDqdjnPnzlG9evVix8/OzsbS0hLIr7fcs2dPli1bRpUqVZQ+GRkZZGVlARAQEICfnx/ffPONUiIiKiqKMWPGoFKpCA8Px8PDA8g/OO/YsWN/7wMAxz9airVN0drSBZxs7KhZqTIABw8eJCUlhaVLl2JlZUVwcDDjxo1j+PDhJcaHhITQoUMHAgMDARg/fjyhoaHMnz+ftWvXMnToUPz9/QHw9/dn9+7djBgxgpycHLZv346trS3u7u60bNmSixcv0qVLl7+9ZiGEEEIIIYQQQgjx16gMZfnv2IX4FxkMBuVAtxdRbm4uGo3x72kSExM5duwYAQEB/9Ksyker1WJnZ8fxSxdKTC4XTiwDzJs3j19//ZUDBw4A+X9Ojo6OPH78uMT3dOjQgR49evDBBx8AcObMGT766CMOHjyIu7s7ixYt4vXXXwdgx44dnDhxosihhHl5edSsWZNVq1bx2muv/a11CyGEEEIIIYQQQoiiCnJFKSkp2NralthPymKI52rdunW0bNmyyPP69euXWOagW7dubNu2TblPSUlBpVKVemDdX/Htt99y6dIlID+BqdPp0Ov1aLVaVCoVWVlZGAwGsrOzycnJUeJ69erF7NmzjcpiJCcnM3HiRNavX1+uOXz44YeYmZlRsWJFKlasiLW1NbVq1SpzfEZGBufOnePBgwflem8B3zmTafHB2GKvehOHczvhT6WvVqvF3d1duVepVKjVapKSkkoc/8kYW1tb7t2799S2wrZu3YparaZnz55/aY1CCCGEEEIIIYQQ4tmQ5LJ4Lj7//HPq1avHxx9/zJUrV2jUqJHRdfPmTQIDA3Fzc+P7779X4u7evcvJkydp164d2dnZ6PV6bGxsUKvVqNXqZzpHV1dXevfuzS+//MIvv/xCq1ateOWVV+jcuTMA7du3x8fHh1atWvHNN98ocWvWrOGbb74hODiY7Oxs8vLyqFOnDvv37+f27dtKv+zsbOXnpUuXKklkOzs7pTSGmZkZb775JsnJySQnJ/P9999jYWFRpvmfPHmSmjVrMnLkSNzd3Vm2bNlf+Aie0KBd0cu9OVnZ2SSmpihdNRoN5ubmRuEWFhZkZGSUOPyTMYX7l9ZW4P79+wQFBbFkyZIi7xZCCCGEEEIIIYQQz5fUXBbPxaRJk5g0aRIhISFs27atSH1gNzc3QkJClERugVWrVjFo0CBq1qxJs2bNWLhwId27dzfqc/HiRZo1a/a359iyZUvWrVvH8ePHmTp1Kv3798dgMJCXl8e5c+fo06cPBoOB3Nxc/Pz8lLjatWtz9OhRTE1NGTZsGLt27cLKyoqcnBzy8vJYv3492dnZZGZmkpSUhLW1Naamprz55pts2bKFBw8e4OXlBeQnl59kYvL03wHp9XqGDRtGaGgoPXr04NixY3Tv3p0xY8aULwlrUQEqVCxTVwcHB6Kjo42epaamFruGwjEJCQnF9i+tDfLXOGTIEPz8/Ojfv3+Z5iiEEEIIIYQQQggh/jmSXBYvrJSUFDZs2EBwcDAApqamSqLUYDAwZ84ctm/fTkZGBvfv338m7+zZs6dSbsHX1xe1Wk1ubi6zZ8+mc+fO6PV6cnNzld3EmZmZ/PHHHzRu3BiAr776Shlr8eLFREdHs2XLliLvefLAwIKazSqVikuXLjF37lwA4uLiyjRvrVZLUFAQPXr0AKB58+bodDrS0tL+sR2+3t7ebNy4UbmPjY1Fp9Ph4OBQasyZM2cYOXIkkP+LARcXF6O2Tp06FWkDmDZtGn/++Sf79u37J5YjhBBCCCGEEEIIIcpJksviuYuIiFB26hYoLjn86aefkpKSYvRs06ZNfPDBB8oO4kWLFvHee+/97Tn16NGD6Oho7O3tuXz5Mm+//TYXLlzAzMwMlUqFo6MjEydOxGAwkJOTg5mZGadPn+b48eMEBAQwdepUpk+fXuRgv9KEhYVx7Ngx8vLyjEp82Nvb06hRIyA/2Xz+/PmnjlWxYkXGjBkD5CfeP/vsM9q2bYujo2Ox/XU6HTqdTrnXarVlnneBdu3aodVq2bx5M8OHDyc4OJjOnTujVqtJTk5WypcU1q9fP1q3bs3EiRNxd3dnxYoVDB48GICAgABGjx7N8OHD0Wg0bNq0ieXLlwP5dZbXr1/PiRMn0Ov1pKWlGf2yQQghhBBCCCGEEEI8f5JcFs9dixYtii2LUVhkZCTr1q0jICCAkydPsnLlSq5evYqXlxfbtm3jpZdeIjg4mMjIyGdSe3n//v0kJiYqSe+NGzdy7Ngxrl69WqRvrVq16Nq1KwDdu3fnxIkTvPPOO4waNQonJyfy8vKK7EyG/JrLhcs8BAQEKGUxfHx8AMjNzcXV1ZWAgAAAnJyc+Pbbb8u8joSEBDw9PUlOTi5SsqKwhQsXMm/evDKPWxyNRkNISAgDBw5kypQpmJiYKH+u9vb2XLx4kaZNmxrFeHp6MnHiRLy8vLCwsMDDw4OxY8cC4Ofnx7fffouHhwcAnTp1om/fvkB+zW6tVms03tChQ4vdFS6EEEIIIYQQQgghng9JLovn7ty5c8rO3AL37t0zuq9UqRIrVqzg3LlzVKlShffff5+xY8fy+uuvU69ePaVfbm5uuXYLl6RgjMJj7dixg/T0dF599VXl2ZEjRzh+/LiSXIb8EhQFu4vDw8Px8/OjQoUKyuF+33//PZmZmdSpU4fIyMhS56HT6fjxxx+V2tNJSUnlWkelSpX4z3/+w6xZsxgwYAC//vorKpWqSL/p06czefJk5V6r1VKjRo1yvQugd+/e3Lhxg4iICHx8fJSd0gaDocSYBQsWMGjQIOLj4/H19VUS7iqVitDQUCZMmEB6ejq+vr7K3C9evFjuuQkhhBBCCCGEEEKIf5Ykl8U/Tq/XYzAYlB3G3t7eJe5c1uv15OTkUK1aNQYNGsS5c+ewt7enefPmRcb96quvWLduXZFE9bOi0Wg4fvy40e7lhIQEOnToUKTv7t27SUhI4J133iE7OxsoveYy5Jd62LZtGwDVq1cH8utMjxo1ig8//BCAY8eOMX78+HLNu0GDBmzfvp2KFSty+fJlPD09i/QxNzd/ZiUlnJ2d6dWrV7liGjZsSMOGDYtt8/b2fhbTEkIIIYQQQgghhBD/MJN/ewLi/75z587xyiuv0Lp1a7Zs2UJubi5t2rQxuqpXr87cuXNp27YtrVu3Jjk5ucTxCnbFNmjQgKFDh7J161aj9uzsbBITE0lLS/tL8/3999/ZtGkTKpWKiRMncv78eeWaPn16kf56vZ45c+aUawe1wWDgrbfeIjc3l7t376LX6wGIjo6mfv365Z7z1atXGTp0qHKvVqsxMTEpf8mQrHRITy56ZRX9ltHR0Xh7e2Nvb8+UKVNK3a1cICwsDFdXV6pVq8aOHTuM2lavXk2VKlWoVasWR48eVZ6npaXx+uuvY2Vlha2tLbNmzSrfmoQQQgghhBBCCCHEP0KSy+If9/LLL3P27FlOnz5NWFgYVatW5ZtvvuHUqVOcOnWKOXPm4OHhwffff8/p06c5f/48FStWLHG83NxcPDw88PT0ZOTIkSQnJ7N+/Xpyc3MB2LdvH5UqVSr3jt+cnBy0Wi09e/ZUxlq+fDleXl7KtXDhwiJxO3bsICcnxyi5+zR5eXnKz2ZmZnh5eZGdnU1ERARt2rQpMS4jI4PMzMwiz93d3Tly5Ajz5s3jzp07fPjhh7i7u/PSSy+VeU4A3IqE304UvWIvYGFmhpONHZBfvsPPz48WLVpw/vx5YmJinlr/ODo6mkGDBjF79mzCw8OZM2cO165dA/LLiQQFBbFhwwa2bdtGYGAgjx49AmDSpElkZmZy5coV9u7dy5IlSzh8+HD51iWEEEIIIYQQQgghnjlJLovn5sSJE3h5eVG5cmUcHByU5y+99BIJCQk0atTIaMcq5O8KLkjEmpqaEhcXh6mpKb/99hsmJvn/9/3hhx/46KOPlPu/av/+/ahUKjZt2sSoUaPIzc196s7llJQUPvjgA2bNmoVKpTJKGj8pNzdXKZnx8ssv079/fwAcHBzYtWsX+/bto2bNmri4uBjFFa6ZPHbs2GJ3T5ubm7N//35++OEHGjRowPnz55X1lMfxj5YS8emaYq9ryzdTs1JlAA4ePEhKSgpLly6ldu3aBAcHs2nTplLHDgkJoUOHDgQGBtK4cWPGjx9PaGgoAGvXrmXo0KH4+/vTqlUr/P392b17t1ImZfv27bi7u9OhQwdatmwpNZiFEEIIIYQQQgghXgBSc1k8F0uWLGHhwoVs3LiR1157zajNxcWF77//npUrV9KzZ09OnTqFl5cXkL9DVqvVAjBy5EimT5/Oe++9ZxRvY2PDkiVLlORyQEAAK1euJD4+vlxzHDp0KB06dKBBgwZA/k7mwn777Tfmzp3LlClTlGeLFi3C3NycgQMHcvLkSbp27YqZmRlqtRqDwYDBYGDPnj3k5OSQnZ2Nn58fu3btwtvbm7S0NGbOnMlHH31EVlYWs2bNYty4ccrYq1ev5ptvvlEOyQNK3B2ck5ODp6cnZ8+eVZ7l5eWRk5ODqalpmb9BU/fa2NraPrVfZGQkPj4+WFlZAdCkSRNiYmKeGtOjRw/lvmXLlnz00UdK25tvvmnUduLECQIDA43WnJeXxx9//IGHh0eZ1ySEEEIIIYQQQggh/hmSXBbPxcCBAwkICMDV1bXEPu+++y5du3alXr16yrP169crPw8bNoxhw4Y99V1JSUl88cUX7Nu3r1xzrFChAg0aNGDGjBnodDo2bdrE+vXrad++PU2bNiUjI4MpU6bw5ZdfMnfuXBYtWsS8efNISUnh3r171KlTh06dOrFr1y4sLCwwGAwkJiZy8+ZNLl26xE8//cTKlSuV91lYWLBnzx5sbW157bXXqFixIu+//z5LliwB8ktgpKWl0b59e6N53r17lypVqlC/fn127dqFp6cnM2fOZP/+/eh0Oh4+fIibmxt6vZ7XXnuN4ODgMn+DS7E3sLaxLvLcycZO2bUMoNVqcXd3V+5VKhVqtZqkpCTs7e2LHfvJGFtbW+7du/fUtsK2bt2KWq2mZ8+eZV6TEEIIIYQQQgghhPhnSHJZPBfVqlUrU7/CieW/yt7enl9++QUzM7NyxeXm5qLT6TAxMaFixYqkp6cTHx9P9+7dmTZtGu+99x4VKlTg8uXLjB49GisrK0xNTXFzc6NLly7Y2toycOBAdu3axcSJE6lZsyZ//PEHvXr14ttvv2XlypVKWQwAjUbD+vXrycvLo27duqxcuZJ3332XX375Remzc+dODh48aDTPNm3acPjwYczNzdFoNGRkZLBo0SI+/fRTDhw4wBdffEFYWNhf+na+cyaDadF/FizMzIzKYmg0GszNzY37WFiQkZFRYnL5yZiC/k9rK3D//n2CgoJYt25dkXcLIYQQQgghhBBCiOdPksvi/6TyJpYBzp8/j7+/P5mZmRgMBv744w/c3d35+OOPuX79ulIuws3NjYcPH+Lj4wPkl+tYtmwZderUYdKkSXzzzTf069ePmTNn0rdvX7766isOHz7M8OHDlaToxx9/zPr169Fo8v8KTpo0CV9fX2Uu7u7uyq7tJ+smm5qaotFoMDEx4bXXXsNgMHDy5EmcnZ25c+cOtWrVKv8HK+DqCXaOxs+y0siKvUBiaoqSXHZwcCA6OtqoW2pqaqnf3cHBgYSEhGL7l9YG+bW3hwwZgp+fn1KrWgghhBBCCCGEEEL8u+RAPyH+y8fHh4cPHzJ58mRmzpzJl19+CcDs2bP54osvlH5xcXEMHToUgCtXrtCxY0cCAwO5cuUKgNHBggUJUnt7e9LS0pTnH3zwAbGxsVy7do3MzEyjxDJAdnY2VapUKXaeJiYmSsJ53759/P7771hbW9OlSxc2btzIsWPHCAgIoEePHpw+fbp8H8GiAlSoaHxZFC2T4e3tzZkzZ5T72NhYdDqd0UGNT4u5ePGicnhhaW0A06ZN488//2TNmjXlW48QQgghhBBCCCGE+MdIclmIUhgMhlLb8/Ly+Pjjj5k3bx55eXnEx8ej1+tRqVTo9XrlMD0nJyceP36sxJmbm2NqasqqVauoXbs2TZs2NRpXpVLh5ORU5H0TJkzg1q1bdO3aldjYWPz8/Khbty67d+/m5MmTnD9/nrNnzxIWFoZarSYlJaXYeRcclFj4Ko927dqh1WrZvHkzAMHBwXTu3Bm1Wk1ycjJ5eXlFYvr168fOnTuJiooiLS2NFStW0K1bNyD/EMY1a9YQHx/Pw4cP2bRpk9K2detW1q9fT2hoKHq9nrS0NHQ6XbnmK4QQQgghhBBCCCGePUkuC1GMa9eusXTpUkxMTPjkk0+oWLEia9euZfLkyVSsWJGdO3diMBho0qQJfn5+ZGdnY2ZmRlRUFDk5OZibm5Obm6skl6tWrUp8fLzRO65fv868efPo2bMnV69eVRKyBoOBR48eKcnlwonaZcuWcf/+fa5du8Zbb73Fjz/+yLVr13jjjTeUPk5OTkrJisK7qAtbuHAhdnZ2ylWjRo1yfR+NRkNISAjjx4/HycmJvXv3smjRIiB/l3ZUVFSRGE9PTyZOnIiXlxcuLi6o1WrGjh0LgJ+fH506dcLDwwN3d3eaNWtG3759Afj888/RarU0bdoUGxsbbGxsGDVqVLnmK4QQQgghhBBCCCGePUkuC/Fff/zxB9OnT2fz5s1cvnyZl156iRkzZpCYmEhycjJjxoxh6dKlJCcnk5yczPDhw4H8ZHBgYCDp6encuXOH7OxszM3NycnJUZLLtWrV4urVq8q77t+/j7+/P6mpqVy4cIFhw4YpB9hdv34dOzs7pT5zVlaWEmdiYsKbb77Jtm3bOHXqFJmZmbzzzjtERkYqfR4/fkzlypVLXev06dNJSUlRrjt37pT7e/Xu3ZsbN27w5Zdf8ttvv9GwYUPlezy5E7vAggULuHjxImFhYfz8889YWloC+Tu1Q0NDOX78OAcOHGDfvn1K6Y+LFy9iMBiMri1btpR7vkIIIYQQQgghhBDi2ZLkshD/pdfrefjwIZ07d6Z///5069aNzz//HGtra6ytrdm2bRuzZs3C1tYWS0tLEhISyMzMZNCgQeTl5TFq1ChSUlJISkrC1taWjIwMJUH80ksv8euvvyrvmjp1Ku7u7nTr1o23334bPz8/6tevz1dffcWPP/5I1apVefvtt/H392fdunVK3N27d4mIiKBfv36o1Wri4uLYs2cPdevWBSA3Nxe1Wo2j4xOH8j3B3NwcW1tbo+uvcHZ2plevXk99X2ENGzakS5cuxR7+5+3tTfv27YscYiiEEEIIIYQQQgghXjySXBbiv+rWrcsXX3xhVCLigw8+YMWKFbRv357ExEQSExPp2bMnEyZMoFKlSvz0009UqFCBrVu3kpWVhUaj4d69e9SuXZv09HQsLS3R6XT4+Pjw/fffKyUulixZwv79+7GwsEClUjFz5kwqVaqEq6srGzduZPTo0fz2229YWloaJW7j4uKYO3cuVlZWAEyePJmgoCCl/MXNmzepWbMmarUayE82l0tWOqQnG19ZacV2jY6OxtvbG3t7e6ZMmfLU+tQAYWFhuLq6Uq1aNXbs2GHUtnr1aqpUqUKtWrU4evRokdjFixczbNiw8q1HCCGEEEIIIYQQQvxjJLksxFMMGTKEqKgodu/eTWhoKNHR0cydOxeAnj17snHjRtRqNTdu3KBmzZqcP3+eOnXq8PjxY+zs7BgwYAB//PEHLi4uHDx4EIBKlSopCeDCVqxYQevWrfH09FSeabVaNmzYQF5eHm3atGHs2LGkpaWRkpJC3bp1+eCDD7C0tOTHH38kJCSEXr16ER8fT1BQkNE4ZXIrEn47YXzFXsDCzAwnGzulm06nw8/PjxYtWnD+/HliYmKeWqoiOjqaQYMGMXv2bMLDw5kzZw7Xrl0DIDw8nKCgIDZs2MC2bdsIDAzk0aNHSuyWLVuYNm1a+dYihBBCCCGEEEIIIf5Rmn97AkK8aJ7cgWtpacm2bdvo2bMnFhYWnD17VqkVXODmzZscOXKEadOmceXKFTw9PVm8eDE3btwgJyeHzZs3M3z4cGbMmEHPnj2VncZ5eXno9XoA9u7dy759+zhw4ACXL18mKSkJg8FAdHQ0M2bM4O233yYrK4vdu3czc+ZMXnnlFUJCQlCpVGg0GmJiYvj666+JiIjgjTfeoHLlymzYsKFcaz/+0VKsbayLPHeysaNmpf/VcT548CApKSksXboUKysrgoODGTdunFKHujghISF06NCBwMBAAMaPH09oaCjz589n7dq1DB06FH9/fwD8/f3ZvXs3gYGBHDt2jBUrVjBixAiys7PLtR4hhBBCCCGEEEII8c+RncvihbdkyRJCQ0PL3L9wKYjHjx8bHaQHcOjQIZKSkoqNHTZsGGvWrKFKlSrExsby6aef8uabb9KvXz969uxJ/fr16dGjB6NHj2b+/PkkJiayatUqmjVrxsyZMwkJCeGtt97C1NSU+vXrExgYyBdffMGpU6cYMmQIjRo1Ug7ug/zD+rKzs9m8eTNffPEF+/fvx9LSktq1a/Pnn39ibW1N+/btmThxIiqViuXLlzNr1izmzZvHV199hZWVFfHx8Xh7e7N27VqOHz+Ok5MT33//PSqVih49epTrWzd1r03zWh5FrsKJZYDIyEh8fHyU8hxNmjQhJiam1LEjIyPp2LGjct+yZUsiIiKe2lavXj3OnDlDtWrVyrUWIYQQQgghhBBCCPHPkp3L4l+Rm5tL165dGThwIG+//XaJfTQaDS+//DL9+vWjX79+WFpaotfr+eyzzzh16pTS18vLi7lz5/Lw4UNat27NF198Qbt27bhw4QITJ07k0qVLmJqaotPp6NOnD6dOncLLy6vIOwcPHszIkSNp27YtGRkZ/PLLL+zevZuHDx9y6tQpzM3NqVy5MkeOHOHx48c4OTnRu3dv+vXrh5eXF3v27KFOnTrs2LGDXr168Z///IdvvvmGIUOG8OmnnxIUFIS19f92Bh8+fFj5eceOHbz33nuEhITg5OREQkJCkflNnTqVoKAgZs6cyY4dOxg4cCDOzs58/vnntGzZUjkkz9LSki1btvD777+X68/lUuyNIjuXn9y1DPmlOtzd3ZV7lUqFWq0mKSkJe3v7Ysd+MsbW1pZ79+49ta1q1arlWoMQQgghhBBCCCGEeD4kuSz+FYsXLyY+Pp5FixbRo0cPqlevXqRPgwYNePjwIaamphgMBqpWrUp2djZz587l6tWruLm5MWDAACZPnqwkVatUqcJnn33GgAEDiImJoXPnzgwcOJCUlBScnJw4duwYZmZmHDp0iB9++IGcnBymTZvGqFGj+PHHH6lQoQIGgwEbGxuio6NZvXo14eHhVK5cmXr16tG3b19++uknpk+frsyzR48eWFlZkZiYyLBhw3j99ddZt24dJ06cYP369ezatQtnZ2dq1qxZYiIdwMLCAhsbG6NnOTk5mJiYGNVnVqvVJCQkkJqaik6n4+zZs4wdOxYzMzOuXbtG9erVsba2Ji8vr9xlMXznTAZT438WLMzMuLZ8s1GCWaPRYG5uXmT+GRkZJSaXn4wp6P+0NiGEEEIIIYQQQgjxYpLksnjuvvnmGz799FNOnz7NsWPH8PPz48CBA0V2qEZGRjJ69GjWrl1LhQoVWLp0KadPn2bq1Km8++67uLq60rp1a27evEn37t2VuNdee43OnTszYMAArl27RoUKFfjuu++oW7cuFhYWvP7667i5uZGbm0tOTg5qtZrt27cr8REREYwcORIAe3t7cnJyAHjppZf45ZdfOHXqFDqdTtlpe+XKFQDc3Nz47rvv2LhxI2PGjMHDwwNTU1NsbGz47bffqFu3LrVr1y7xu5iYmLB8+XJWrlypPMvLy+PMmTP4+PiQlZXFoEGDsLGx4ddffyU6Opoff/yRDh06EBUVRV5eHs7Ozvz88884ODj8tT8cV0+wc/zffVYaWbEXSExNMUouOzg4EB0dbRSampqqJPmL4+DgYLQbu3D/0tqEEEIIIYQQQgghxItJksviuTEYDKxevZrp06ezc+dOGjRoQIMGDbh+/TotW7Zk+fLl9O3bV+lvZWVFREQEq1atYurUqfznP/9R6vIW7OS9cuUKZmZmNGvWDIDExEQeP35M3bp1+eGHH+jatSszZsygffv23LhxA29vb/74449ik69Xr16lfv363L17V9lJffv2bTQaDaNHj+bXX3/l1q1bNG3alAULFuDu7k5WVhYGg0FJhJ4/f55Dhw5x7tw5MjMzlYP7jh49ip+f31O/0eTJk1m8eLFyn5OTg0qlAvJ3827duhUzMzPeffddfHx8GDBgACqVigkTJhAeHk5KSgrt2rUDoEOHDkaJ6jKxqAAVKj61m7e3Nxs3blTuY2Nj0el0pSa1vb29OXPmjJK4v3jxIi4uLkZtnTp1KtImhBBCCCGEEEIIIV5McqCfeC5OnTpFx44dmTdvHocPH6ZXr15K2+eff86cOXMYPnw4zZs3Z9GiRaSkpJCbm8uECRO4efMmqampnDp1iqFDh5KVlaXEHjlyhJ49eyoJ2MOHD+Pl5cXy5csxGAzk5eUpfU+cOMFLL71E3bp1cXJywsnJiXfffReABw8e4Ovry8WLF7l58yZ169alfv36tG/fHlNTU6pUqcK2bdu4du0aR48e5ZVXXgFg5syZNG/enKZNmwIwcuRI1Go13t7eDBkyRHn3oUOHePXVV5X7gqT005iamqJWq5Xd0wMHDuSHH35Q2ufNm8fKlSu5f/8+CxYsIDs7m+joaIKCgnjw4EGJ4+p0OrRardFVHu3atUOr1bJ582YAgoOD6dy5M2q1muTkZKPvXqBfv37s3LmTqKgo0tLSWLFiBd26dQMgICCANWvWEB8fz8OHD9m0aZPSJoQQQgghhBBCCCFeTJJcFv+4W7du0aNHD+rUqUPdunXp1q0bFStWxMLCAnNzcypWrMj7779P3bp16dWrF3v27OHSpUs4OTkxc+ZMvvvuO9zd3TE1NaVevXq0atVKGTsmJsaoVu/AgQP5+eefOXnyJDqdjpycHN58801sbGzIzMzk6NGjPHjwgF9//RVbW1u6dOkCgLOzM2vXriUgIIBjx47RrFkz/vOf/3Dv3j169uzJSy+9RPXq1XF3d+fkyZPK+5YsWcJvv/3G7t27sba25rvvvuPy5ctcuXKFsLAwALKzs7l9+7bRQX6WlpaYmpqi0WiUa9++fSxdutTomUajwcTEhIEDBwL5tYkrVqyojGNubo65ubmyQ/rdd9/l888/BzCq0/ykhQsXYmdnp1w1atQo15+pRqMhJCSE8ePH4+TkxN69e1m0aBGQX0okKiqqSIynpycTJ07Ey8sLFxcX1Go1Y8eOBcDPz49OnTrh4eGBu7s7zZo1M9rFLoQQQgghhBBCCCFePCpDWbZPCvE3PXr0CEdHR6Nnc+fOJTExkVWrVpV7vPfee4/q1aszcuRIWrZsyYwZMxg+fHiRfk2aNGHnzp2sWLGCl19+WenTrFkz3nvvPYYOHWrUf8SIEWzevJm4uDhcXV0B+PTTT3n06BHVqlVj586dnDlzxihm9+7djBo1itzcXGrVqgXkl7A4deoU9evX5/vvv+fPP/9k0KBBXLhwAXt7e/R6vZIQLtCnTx/q1KnDZ599puzELpCVlYWFhQX9+vVj7NixfPXVVzRo0IC4uDjq16/PqVOnCAgI4MiRI7Ro0QJTU1MOHTrEzp07i/1+Op0OnU6n3Gu12vwE85QZ4OD8v47pyfDbCSI+XUPzWh5Fxnnw4AERERH4+PgU+fMtSUxMDPHx8fj6+hapq3zu3DnS09Px9fUt8g2EEEIIIYQQQgghxPOh1Wqxs7MjJSUFW1vbEvtJzWXxXDg6OpKXl4dKpSqSVC2g1+vR6/VoNPn/t7x06RJ+fn5GO3BdXFw4ffq0cm9vb8/69evp378/AwcOxMLCggsXLvDRRx+xZ88ekpKSlJ2+KpWKFi1akJmZSWxsLB999BHz5s3j6NGjuLm5AdCoUSMA/vOf/zBixAgAunTpQkBAAJmZmXz55ZdGc546dSqhoaHY2tryxx9/KM+f/EvXqlUr/P39+eyzzwgODi7xG2RnZ9OkSRMGDhzIpEmTsLS0BPKT1QXfaMCAAWRnZ+Pk5EReXh516tRRSmxkZGTg7OzMo0eP0Ov1Jfxp/G/H89/l7OxsVOKkLBo2bEjDhg2LbfP29v7bcxJCCCGEEEIIIYQQz4eUxRDPzYYNG3B1dcXNzQ03NzeWLVvG1q1blXtXV1ejA+j0ej3m5ubExcURFxdHWFgYjx49KjJus2bNSEpK4vbt2wD89NNPODo6kp6ejlarpWrVqkrfiIgIYmJiqFevHtu3b+fmzZtKYjkpKYng4GAWLVrE1KlTefjwIQCNGzfm0aNHvPLKK0oZjQJTpkzh/Pnz3Lt3j86dOytXQYK8sIYNGxZbLqIwMzMz9uzZw88//0yDBg3YvXu3Ufvu3btJSEhg4MCBzJ49m3Xr1tG4cWNyc3OB/IS8h0f+DuOCOs3lkpWev1u54MpKK7FrdHQ03t7e2NvbM2XKlDLVkA4LC8PV1ZVq1aqxY8cOo7bVq1dTpUoVatWqxdGjR4vELl68mGHDhpVvPUIIIYQQQgghhBDiHyPJZfHcjBkzhjt37ijJ4vfee4+33npLub9z5w6TJk1S+puamhYZ48k6wkOHDqVevXo0aNBAKUnxww8/0L9/f44cOULz5s3LVF6hoDZzv379+OCDD3jttddYtmwZ2dnZDBw4kJo1axIdHU1KSgopKSlcunQJACcnJ6ysrKhWrRqHDh1SrsKys7Pp2LEjQUFBvPHGG6XOw2AwULt2bb7//numTZtGSEgImZmZJfZ/+PAhTZs2Zd68eQDk5uaSkJBAlSpVmD59+lPXXcStSPjtxP+u2AtYmJnhZGNn1E2n0+Hn50eLFi04f/48MTExbNmypdSho6OjGTRoELNnzyY8PJw5c+Zw7do1AMLDwwkKCmLDhg1s27aNwMBAo18kbNmyhWnTppV/PUIIIYQQQgghhBDiHyNlMcQLKzc3l7i4OKpXrw7kJ4Dt7e0ByMvLA6Bv37707NkTf39/NBoNt2/f5uLFi3To0IEuXbowePBgANLS0oxKURTs9C0wdOhQbt26xbfffgvkH3iXkJCAr68vLi4uXLhwgVGjRtGlSxe6d+/Orl27iI6OVuZ1584dmjZtWmT8nJwczMzMmD59Oo0aNTLaRf2kvLw8o3mNHj2a0aNHF9v3/v37zJgxA3d3dzp06EBubi5TpkwhNDSU2NhYJk2aREhIyNM/8hOOf7QUaxtro2dONnbUrFTZ6NnBgwdJSUlh6dKlWFlZERwczLhx44qte10gJCSEDh06EBgYCMD48eMJDQ1l/vz5rF27lqFDh+Lv7w+Av78/u3fvJjAwkGPHjrFixQpGjBhBdnZ2udckhBBCCCGEEEIIIf4ZsnNZPBcTJ06katWqRmUx1qxZw9dff63cOzs7Y2Vlxfbt24H8GsmvvPIKd+/e5e7duxw+fFg5NC4rKwvIT0K+8cYbSk3iDRs28PLLL7N3717u3r3LkCFD6NGjB9HR0bRr1447d+7Qs2dPbty4gYuLizK/999/nz179mBtnZ9YdXR0ZNeuXTRo0ICdO3ei0WjYsGEDLVu25OOPP2bKlClKrE6no0aNGkRHRytX4eQy5NdtLi2xXLAmrVb71G+Zl5fHtWvXmDx5MqdOneLo0aO8+uqrbNy4kTZt2jBkyBAlMRsXF1eWPx5FU/faNK/lYXQ9mVgGiIyMxMfHBysrKyD/4MSYmJhSx46MjKRjx47KfcuWLYmIiHhqW7169Thz5gzVqlUr11qEEEIIIYQQQgghxD9LZShLoVQhnpPs7Gz0er2SLC4vg8FAbGwstWrV4s6dO9SoUYOcnByjEhtffPEFbdq0oW7dun/pHY8fP8bBwUG5z83NJSMjQznEr27duqxYsYLu3bsDMHnyZLRarbKTOCcnB41Gg0qlIjAwkH379lG5cn4C9+7du1hbWyuHEN69e5cFCxYwbtw4ozlkZ2djZmYG5NeKzs7OpkqVKkZ9kpKSlJ3eT1NwAujxSxfKtHP5/fffJysri9WrVyvPKlWqxPXr10t8Z4sWLZg2bRr9+/cH4MqVK7z55ptERkbi6OjIoUOHlAP9fvjhBzZs2MDevXuV+Llz5xIXF/fU8htCCCGEEEIIIYQQ4u8pyBWlpKQoOa/iSFkM8UIpSJj+VSqVSqm9XKNGDaBo7eYRI0b8rXcUTixDfr3gvn37UqFCBUxMTEhOTuaNN95Q3puRkYHBYGDPnj3k5eWRnp5OVFQU9erVw8zMjLFjxzJ37lwABgwYQPfu3ZWD6wYMGGCUaB82bBhffvllkTllZGRgYWHB3r176datm/It1Go1p06d4pVXXinT2nznTAZT438WLMzMuLZ8s1GCWaPRYG5ubtzPwoKMjIwSk8tPxhT0f1qbEEIIIYQQQgghhHgxSVkMIf6mXr16odPpePz4MYmJidSuXZu9e/eSmJhIYmIiH3zwAW+99RaJiYnKLuN69eoBYGJiwpo1a2jUqBGNGjXi0KFDzJo1y+i+8CGGa9asISkpieDgYFq3bk1SUhJJSUlYWlrSpk0bTpw4ofQ9efIkNjY2tGzZsuyLcfWEBu3+d7k3Jys7m8TUFKNuDg4OJCQkGD1LTU0t9ZcDT8YU7l9amxBCCCGEEEIIIYR4MUlyWYhnbNasWXh4eNCnTx8OHDhA3759GTp0aLF99Xo9Y8eOVWo1d+/enfnz5xvdF65cY2VlRcWKFbG0tESj0VCxYkWlhEaXLl2MkssnTpygY8eORsnpp7KoABUq/u+ysC62m7e3N2fOnFHuY2Nj0el0RXZ1lxZz8eJFpe51aW1CCCGEEEIIIYQQ4sUkyWUh/iaDwYBer1fuhwwZgouLCyYmJuzdu5cmTZrQqlUrpT0vL0/5uXBcSQoOB3yaLl26cO7cOeWww5MnT9KlS5di++p0OrRardFVHu3atUOr1bJ582YAgoOD6dy5M2q1muTkZKM1FujXrx87d+4kKiqKtLQ0VqxYoZTwCAgIYM2aNcTHx/Pw4UM2bdqktAkhhBBCCCGEEEKIF5Mkl4X4m06fPo1arcbGxsZoN/GRI0fYsWOHcl+xYkVsbGwwNzcnLS0NgMqVKxMWFlZiWYzo6GisrYvfPfykZs2aYWNjw6+//kpGRgYXLlwoMbm8cOFC7OzslKugPnVZaTQaQkJCGD9+PE5OTuzdu5dFixYBYG9vT1RUVJEYT09PJk6ciJeXFy4uLqjVasaOHQuAn58fnTp1wsPDA3d3d5o1a0bfvn3LNSchhBBCCCGEEEII8XypDIX/m3shRLnl5eWh1+tJT0/H3t6epKQkpVRFSXJzc5V+hQ8cfPJAP8jf3ZydnW10sN+yZcvYs2cPx44dMxp34MCBNGjQgFatWvH2228TGxtb7Pt1Oh06nU6512q1+QnmKTPAwfl/HdOT4bcTRHy6hua1PIqM8+DBAyIiIvDx8cHR0bHUNReIiYkhPj4eX1/fInWVz507R3p6Or6+vqhUqjKNJ4QQQgghhBBCCCGeLa1Wi52dHSkpKdja2pbYT/Mc5yTE/0lqtbp8dY2B27dv4+3tTYUKFTAxMcFgMHD79m0sLCw4dOgQb7/9tlJzOCsri5YtW7Jv376njtulSxe++uor8vLy6Nq1a4n9zM3NMTc3L9eci+Ps7EyvXr3KFdOwYUMaNmxYbJu3t/ffnpMQQgghhBBCCCGEeD6kLIYQ/4JatWrx6NEjbt++zc2bN+nVqxdvvPEG/v7+LF26FE9PTz788EPi4uJ48OBBmRLLkJ9c/uWXXzh8+HCJJTFKlZWev1u54MpKK9IlOjoab29v7O3tmTJlCmX5jx/CwsJwdXWlWrVq7Nixw6ht9erVVKlShVq1anH06NEisYsXLzbayS2EEEIIIYQQQgghXgySXBbiX3T27FnatWvHgwcP+OKLLwAwMTHh22+/ZcGCBbz11ltERkaWebwaNWpQvXp1fv31Vzp27Fj+Cd2KhN9O/O+KvYCFmRlONnZAfjkNPz8/WrRowfnz54mJiWHLli2lDhkdHc2gQYOYPXs24eHhzJkzh2vXrgEQHh5OUFAQGzZsYNu2bQQGBvLo0SMldsuWLUybNq386xBCCCGEEEIIIYQQ/zgpiyHEM5KXlwdAeno6Gk3Rv1o5OTmo1WpsbW1JTk6ma9eu3Llzh+DgYIYNG4ZKpUKv15Obm4u7uzuXLl1i0aJFdOjQAS8vL3788ccyzaNLly7Y2tri4OBQ7jUc/2gp1jbGBwg62dhRs1JlAA4ePEhKSgpLly7FysqK4OBgxo0bx/Dhw0scMyQkhA4dOhAYGAjA+PHjCQ0NZf78+axdu5ahQ4fi7+8PgL+/P7t37yYwMJBjx46xYsUKRowYQXZ2drnXIoQQQgghhBBCCCH+WbJzWYi/Sa/Xk5OTg06no0KFCtSrVw9nZ+ciV5UqVRg3bhwAFStWZP78+cTGxjJ8+HDl8LqcnByysrIAsLa25uOPP+bevXusX7/e6J3vvfceBw8eJDo62uh5dHQ0n376KWfPnv1La2nqXpvmtTyMroLEMkBkZCQ+Pj5YWVkB0KRJE2JiYkodMzIy0mgXdcuWLYmIiHhqW7169Thz5gzVqlX7S2sRQgghhBBCCCGEEP8s2bksRDEyMjK4evUqZ8+eJTExkVmzZpXYNyoqildeeQVTU1Nlx3LB7uWCQ/P0ej3du3cnNDRUievatSvz5s0jMzOTTz75BIPBwHfffYeJiQlz584lKyuLTz75BAsLC9zd3ZU4g8GASqXi999/p0ePHsTHxxuNGR4eTuPGjTEYDBgMBkxMyv47pEuxN4x2LhfetQz5J4UWnotKpUKtVpOUlIS9vX2xYz4ZY2try717957aVrVq1TLPWwghhBBCCCGEEEI8f5JcFqKQFStW8PHHH5OVlUVeXh79+/fHw8MDvV5fYpLW09OTtLQ09Hq9klzu06cP7du357333gMgNjbWKIm6c+dO0tLSMDc3x2AwMGrUKJo0acKyZcuwtrYmISEBvV7PkSNHSEtLY+XKlXTp0oUbN27QsGFDLC0t0ev1pKWlUbFiRWVcrVZL69atMTExISsriwULFvD++++Xef2+cyaD6f/+WbAwM+Pa8s1KgrlwwlzpY2FBRkZGicnlJ2MK+j+tTQghhBBCCCGEEEK82CS5LEQhI0aMYMiQIeh0Onx8fPjyyy+VNo1GoyRydTodHTt2ZO/evQAEBQVhbW3NRx99VGTMvLw8OnXqxLRp03jnnXcAePnll2nTpg1DhgwhJSWF3bt389lnn9GzZ09yc3PZsGEDOp2Od999l9zcXBo0aABA7dq10el0AFy+fJnevXsTFxfH6dOn8fT0pFGjRuzfv5/GjRv/tQ/g6gl2jvk/Z6WRFXuBxNQUJbns4OBQpBRHamoqZmZmJQ7p4OBAQkJCsf1LaxNCCCGEEEIIIYQQLzapuSxEIebm5kV24Op0OnJycjA3N+fu3bskJiaycuVKoyToq6++yieffMKFCxeKjLlz506Sk5Pp37+/8szd3Z3169ejVqvJzMxk5cqV2NraEhoaysKFCzl+/DinTp0iODiYxYsXFzvXOnXqsH//fgA6duzI1atX2b9/P7Vr1/7rH8CiAlSomH9ZWBdp9vb25syZM8p9bGwsOp2u1MMDn4y5ePEiLi4uT20TQgghhBBCCCGEEC82SS4L8V95eXm4urri6upKkyZNuHv3Lm5ubtSqVYvQ0FBMTU2N+qvVauXnjh078vrrrzNmzBgMBoPyPDU1lalTp/Lhhx8aJa0XLVrEiBEjWLZsGbt27eLtt9/mq6++wmAwULduXRwdHXFwcKBevXq4ubkRHBxs9O65c+dSs2ZNOnTogJOTE9nZ2XTt2pUOHTpQs2ZNPv7441LXqtPp0Gq1RldZtGvXDq1Wy+bNmwEIDg6mc+fOqNVqkpOTycvLKxLTr18/du7cSVRUFGlpaaxYsYJu3boBEBAQwJo1a4iPj+fhw4ds2rRJaRNCCCGEEEIIIYQQLzZJLgvxX2q1mnv37nHr1i1GjBhB9erViYqKIj4+nhEjRjw1fvbs2eTl5ZGWlqY827t3Lw4ODowbN86o79SpU/n9999Rq9VMnjyZpKQk6tatS7169ahTpw4jR45k9OjR1KlTBw8PD+rUqWMUb2Zmxvjx40lMTCQxMRELCwtu3bpFYmIiQUFBxSZ5C1u4cCF2dnbKVaNGjTJ9I41GQ0hICOPHj8fJyYm9e/eyaNEiAOzt7YmKiioS4+npycSJE/Hy8sLFxQW1Ws3YsWMB8PPzo1OnTnh4eODu7k6zZs3o27dvmeYihBBCCCGEEEIIIf5dUnNZiCckJSWxfv167Ozs6N+/Pz179mTChAnF9s3LyyMvLw8zMzPq1avHmTNnjHY4Dx48mO7du6PRaMjLyyMnJwcLCwsANm7cSFpaGr/99htt2rThp59+Yvr06dy5cwdr6/ySFNnZ2SQlJXHnzh2j9z55uGBubq4SUxbTp09n8uTJyr1Wqy1zgrl3797cuHGDiIgIfHx8cHTMr9FceMf2kxYsWMCgQYOIj4/H19dXKSmiUqkIDQ1lwoQJpKen4+vri0qlMoqdO3dumdclhBBCCCGEEEIIIZ4flaG0jJAQ/w8aO3Yst27d4sqVK+zatYt27dpx/vx5fHx8ePDgARYWFmzZsoVDhw4xYsQI+vTpU+QQuvT0dDQaDebm5sqz3Nxc1Go1KSkpPHr0iMaNG9OhQwc8PDy4ffs2NWrU4MKFC9SvX1+pm/zo0SO+/PJLrl+/DsD8+fNZu3YtGRkZGAwG5YDBW7du4erqCkBKSgoGgwFra2s++eQTBg8e/NQ1a7Va7OzsYMoMcHD+7yKS4bcTRHy6hua1PP7mVxVCCCGEEEIIIYQQ/39RkCtKSUnB1ta2xH5SFkOIQg4dOsS3337LJ598AkDz5s2ZNGkSCQkJxfbv2rUrGRkZJCcnG129evVi4cKFRs/S0tJISUkB8pPEI0aMoHHjxgCsXbuWmTNnYmJigouLC3Xq1KFOnTq4ubkZ7VKeMmUKsbGxJCUlkZycTFxcHD179qRXr17k5uaya9cupe3WrVsMGDCgfB8gKz0/qZyeDFlpxXaJjo7G29sbe3t7pkyZUuqO5QJhYWG4urpSrVo1duzYYdS2evVqqlSpQq1atTh69GiR2MWLFzNs2LDyrUMIIYQQQgghhBBC/OOkLIYQ//X777/zxhtvsG3bNipVqqQ8L3w4Xr169VCpVKSlpdG5c+e//K5PPvkEjUbDZ599BqDscDYYDKxbt86oLEZhhXdC6/V65s6dy08//cS5c+c4deoUfn5+bNy4kZ49exodOFhmtyLB9H//LFiYmeFkY6fc63Q6/Pz86NatGzt37mTChAls2bKF4cOHlzhkdHQ0gwYNYvXq1bz88sv07duX5s2bU69ePcLDwwkKCmLnzp1UqlSJwYMHc+7cOaXUxpYtW5g2bVqZdl8LIYQQQgghhBBCiOdLkstC/Fft2rXZunUrfn5+3Lt3r8iO3OzsbK5du6aUxfjhhx9KHKugFnNJCieT9Xq9UVxISAht2rQB4MqVKwQEBBjFarVa9u/fz+LFi7Gzs+PkyZNYW1vTvXt3vv76a9544w2aN2/O2LFj8fX1xcrKqszf4PhHS7G2+V/tZicbO2pWqqzcHzx4kJSUFJYuXYqVlRXBwcGMGzeu1ORySEgIHTp0IDAwEIDx48cTGhqqlPgYOnQo/v7+APj7+7N7924CAwM5duwYK1asYMSIEUWS7EIIIYQQQgghhBDi3ydlMYT4LxMTEyXJmZmZSUZGhlH7xo0bldrK3bt358MPPyxxrMzMTLKyskp9X1paGj/88AOZmZnKM51Op/wcExND8+bN8fX1NYrx9fVl7dq1zJo1i2PHjuHk5EROTg55eXm0adOG3377jcaNGzNjxgySkpLK/gGApu61aV7LQ7kKJ5YBIiMj8fHxURLWTZo0ISYmptQxIyMj6dixo3LfsmVLIiIintpWcEBitWrVyrUGIYQQQgghhBBCCPF8yM5lIYpRu3ZtEhIS0Ol05OTkYG1tTXR0NOfOnePll18mOTkZD4+SD7k7cuQIAB988AFXr15l3759RfpYWFjw+PFj5VC+U6dOcfLkSaMSEDY2NkYJYmtra3bt2kX16tWpX78+derUwdPTk5kzZ7J//350Oh0PHz7Ezc0NvV7P6tWrCQ4OLvO6L8XeUHYuP7lrGfJ3Tbu7uyv3KpUKtVpNUlIS9vb2xY75ZIytrS337t17alvVqlXLPG8hhBBCCCGEEEII8fxJclmI/7p37x6tWrVS7nv27En16tVJTU1l4cKFRERE0KFDB9LS0mjVqhU///wzlStX5ueff1Zi6tatS926dZV7MzMzJXn8JI1Gw4YNG5TyGebm5jRr1oxffvlF6bNz504OHjxoFNehQwcOHz6Mubk5Go2GjIwMFi1axKeffsqBAwf44osvCAsL+0vfwHfOZKXmsoWZGdeWbzZKMGs0GqO6z5CfJM/IyCgxufxkTEH/p7UJIYQQQgghhBBCiBeblMUQ4r9UKhW5ubnExcUxbdo0UlJSGDx4MKGhoeTl5WFmZoaJiQlffPEF3bt3p379+ly7do233nqLPXv2MHnyZL755ht0Op1RHWUTk//9NcvKyiI3N5ePP/6Y6tWrM3jwYIYOHcry5csxNTVV+rm7u/Pjjz8q8yrM1NQUjUaDiYkJr732Gp6enjx8+BCAO3fuUKtWrb/+EVw9oUE7cG9OVnY2iakpRs0ODg4kJCQYPUtNTVXKhRTnyZjC/UtrE0IIIYQQQgghhBAvNkkuC/FfhZO7Bfc1a9akbdu23L17V3l+9OhRxo8fr/SpVq0aISEhtGrVCjMzM9q2bYu7uztubm6sWrWKsLAw3NzccHNzo06dOhw+fJgPPviA2NhYrl27RmZmplFdZcg/PLBKlSrFztPExERJOO/bt4/ff/8da2trunTpwsaNGzl27BgBAQH06NGD06dPl+8jWFSAChXBwrrYZm9vb86cOaPcx8bGotPpcHBwKHHIJ2MuXryIi4vLU9uEEEIIIYQQQgghxItNymIIUYrs7Gy2bduGWq1Wnu3Zswe9Xk9WVpbRc8hP/J49e1a5nzVrFnfv3mXLli3Fjr9kyRJq165N06ZNuXTpkvJcpVLh5ORUpP+ECRO4desWXbt2JT4+Hj8/P1QqFbNnz+bkyZNGhwi++uqrpKSkFBkD8g8OLHx4oFarLfU7FGjXrh1arZbNmzczfPhwgoOD6dy5M2q1muTkZGxsbIp8k379+tG6dWsmTpyIu7s7K1asUOpKBwQEMHr0aIYPH45Go2HTpk0sX768THMRQgghhBBCCCGEEP8u2bksRCkGDBhA9erVsba25ocffqBr1664ublRo0YNmjdv/rfGvn79OvPmzaNnz55cvXpVqb1sMBh49OiRklwueA6wbNky7t+/r5Tj+PHHH7l27RpvvPGG0sfJyYno6GjAuCRHYQsXLsTOzk65atSoUaY5azQaQkJCGD9+PE5OTuzdu5dFixYBYG9vT1RUVJEYT09PJk6ciJeXFy4uLqjVasaOHQuAn58fnTp1wsPDA3d3d5o1a0bfvn3LNBchhBBCCCGEEEII8e+S5LIQpdi1axe3b9+matWqvPTSS1SsWJHvvvuO+Ph4YmJiitRDBkhJScHa2pru3bvz888/c+vWLbp3746DgwPXr18H4P79+/j7+5OamsqFCxcYNmyYcpDd9evXsbOzUw66K7wb2cTEhDfffJNt27Zx6tQpMjMzeeedd4iMjFT6PH78mMqVK1Oa6dOnk5KSolx37twp8zfp3bs3N27c4Msvv+S3336jYcOGQH5SvGnTpsXGLFiwgIsXLxIWFsbPP/+MpaUlkL9DOzQ0lOPHj3PgwAH27dtX5JvOnTu3xJ3fQgghhBBCCCGEEOLfI2UxhCjkwYMHuLm5kZqaSvfu3QEIDg7mlVde4fHjx3h5eTFz5kwOHjyISqXCYDBw/fp13NzcSExMpGHDhpiampKens6hQ4eMxnZ2dkajyf8rN3XqVNzd3XF1deXtt9/mwoUL1K9fn6+++ooffviBqlWr8vbbb7NixQq6dOmijHH37l0iIiL47rvvWLJkCXFxcezZs4fFixcDkJubi1qtxtHRsdR1mpubK8nrv8LZ2ZlevXqVK6Zhw4ZKIvpJ3t7ef3kuQgghhBBCCCGEEOLfITuXhfivnJwcnJ2diYuLY+fOnTRr1ozvvvuODRs2KMnbAQMGcPfuXSZOnEhOTg56vZ66desSFxdHQEAAOTk5xe5mLlBQpmLJkiXs378fCwsLVCoVM2fOpFKlSri6urJx40ZGjx7Nb7/9hqWlpVGiOC4ujrlz52JlZQXA5MmTCQoKUsa9efMmNWvWVOoe5+bm/iPfSgghhBBCCCGEEEIISS4L8V8ajYYOHToA0LlzZwBGjhxJWFiYUmZCo9Gwd+9evv/+e2rVqkVaWpoS379/f3x9fUtNLheoVKlSkYPvAFasWEHr1q3x9PRUnmm1WjZs2EBeXh5t2rRh7NixpKWlkZKSQt26dfnggw+wtLTkxx9/JCQkhF69ehEfH09QUJDROGWSlQ7pyZCVVmxzdHQ03t7e2NvbM2XKFAwGw1OHDAsLw9XVlWrVqrFjxw6jttWrV1OlShVq1arF0aNHi8QuXryYYcOGlW8NQgghhBBCCCGEEOK5kOSyEP9VqVIlQkNDgfwdv3fu3OHAgQO88sorAOj1egwGA7Vr1+by5cvMnz8fd3d35XC6Xr160aZNG/R6PQDVq1c3uhISEookY/Py8pT+e/fuZd++fSxduhSVSkVSUhIGg4Ho6GhmzJiBiYkJWVlZ7NixgyZNmvDKK6+wc+dOVCoVGo2GmJgYvv76a+bMmcNbb73F+vXrqVixYvk+wq1I+O0ExF7AwswMJxs7pUmn0+Hn50eLFi04f/48MTExT62FHB0dzaBBg5g9ezbh4eHMmTOHa9euARAeHk5QUBAbNmxg27ZtBAYG8ujRIyV2y5YtTJs2rXzzF0IIIYQQQgghhBDPjcpQlq2HQgg6dOjA5MmT8fPzK7WfVqvFzs6uSCLZ2dmZY8eOUb9+feVZly5dGDduHElJSezZs4ft27djbW1NYmIiDRo0ICMjg5ycHGbPns3s2bNZtGgRGzZsYO7cuQwZMgSA+Ph4+vTpQ3Z2Nnv37sXNzY3MzExGjhzJ7du3OXXq1FPXVjDn45cuYG1jDYCTjR01K/3vYMA9e/YwYsQI7t69i5WVFZGRkYwbN67U8d977z2uXr2q1J9evnw5CQkJzJ8/nz59+uDs7My6desAmDRpEi+99BKBgYEcO3aMyZMn4+XlRXZ2thzoJ4QQQgghhBBCCPEcFeSKUlJSsLW1LbGfHOgn/p9y8eJFqlSpQrVq1cod+9NPP5Wpn7W1NXfu3Cny/MGDB0WeNWvWDB8fH5ydnRk2bJhSUsPJyYmEhIQi/adOnUpQUJBRSQ0XFxfWrFlD06ZNMTU1BcDS0pJt27Zx/fr1Ms25LCIjI/Hx8VHqPTdp0oSYmJinxvTo0UO5b9myJR999JHS9uabbxq1nThxgsDAQOrVq8eZM2dYuHAhcXFxz2wNQgghhBBCCCGEEOLZkbIY4v8p7777Lhs2bCix3WAwkJWVRVJSEjdu3ODkyZN89dVXzJkzB39/f5ydnfn5559LfYeJiQnVq1cHoF+/fkyZMqXEvitXrkSr1QIY1WquW7cup0+fLjamcGL5/v37vPrqq3h4eCiJ5cLzKLxLuix850ymxQdjafHBWOpNHM7thD+VNq1Wi7u7u3KvUqlQq9UkJSWVON6TMba2tty7d++pbVWrVsXc3LxccxdCCCGEEEIIIYQQz5fsXBb/J82YMQPIT7ACNGrUiICAAC5evMjmzZtLjHv77bf56quvqFKlCk5OTlSuXFnZ6dyzZ0/eeecdJXH8pPXr13P06FGjWsfm5uZYWFiU+D5zc3NljmvXriUpKYkZM2ZgaWlZpuRqlSpVUKvVDBgwgAMHDihj/WWunmDnCFlpZMVeIDE1RSmNodFoiszJwsKCjIwM7O3tix3uyZiC/k9rE0IIIYQQQgghhBAvPtm5LP5Pql+/vnJdv36dqKgoLl68iE6no0uXLri5ueHm5kbVqlUZPXq0Enf//n2Cg4OJjY3l3Llz9O7dm5s3bzJ//nxGjRpFr169qFmzZrHv7Nu3L48ePcLT01OpQ2xiYmK007g0aWlpJCcnA/m7gq9evcrq1avp168fWVlZQP6hghkZGeTl5Snjb926FRsbG6MyGgX9ys2iAlSoCBbWRZocHByKlOpITU3FzMysxOGejCncv7Q2IYQQQgghhBBCCPHik+Sy+D9pwIABtG3blsGDB2NpaYm3tzd79+5lypQpxMXFKVe1atWMDui7ffu2UakGExOTIgfzFee3337DycmJ8PBwBgwYUGrpDcjfIV1QFL1Zs2b4+/tjamrKzZs3effdd7l+/TqLFy/m4cOH7Nq1S0m6RkVF4ejoiKOjI05OTjg5OVGzZk127drFSy+9pDxzdHSkVq1aJb5fp9Oh1WqNrqfx9vbmzJkzyn1sbCw6nQ4HB4cyx1y8eBEXF5entgkhhBBCCCGEEEKIF58kl8X/Sd999x1du3YlNTWV48eP07x5czZv3sybb75JSEgIq1atQqvVkpubS8eOHQFISEjg+vXr1KlTRxlHpVIZ1UKG/MRswU5igKysLPr06UPnzp25c+cOixYtYuvWraXOb/Xq1SQlJWFnZ8eFCxfo3LkzK1eu5OjRo1hYWFC1alVCQkKKlPfw9PQkMzOT5ORkEhMTSUxMZO/evVStWlW5T0xMJCkpqdgDBAssXLgQOzs75apRo8ZTv2m7du3QarVKWZHg4GA6d+6MWq0mOTlZ2U1dWL9+/di5cydRUVGkpaWxYsUKunXrBkBAQABr1qwhPj6ehw8fsmnTJqVNCCGEEEIIIYQQQrz4JLks/k8aOHAgPj4+9OrVC0dHRypVqsRnn31G48aNuXjxIpcvX8bW1pbIyEgsLS0B+PLLL8nOzqZRo0ZoNBo0Gg2jRo3i+PHjyr1Go8HCwsKolIaFhQVnz57F2dmZxo0bc+TIkafOz8zMTEkYFxyM17BhQ9555x0+++wzbGxsSozV6/VP3U1dXKK3sOnTp5OSkqJcd+7ceeqcNRoNISEhjB8/HicnJ/bu3cuiRYsAsLe3JyoqqkiMp6cnEydOxMvLCxcXF9RqNWPHjgXAz8+PTp064eHhgbu7O82aNaNv375PnYcQQgghhBBCCCGEeDHIgX7i/6xVq1ZRp04dXn/9dSwtLXnzzTeB/LrKxZVyGDVqFAEBAdSoUYOMjAxsbGwICQlh27ZtHDt2TOlnMBjQ6/VGsXZ2dmzfvp19+/bRqlWrImPn5ORw9+5dbt68SadOnYq0jx07luzs7CK7jZ98D+Qf/Pf+++9jbm6OSqUiNzeXjIwM5RBBvV5PZmYmsbGxJR4+aG5uXqYDA5/Uu3dvbty4QUREBD4+Pjg6OgKUmuxesGABgwYNIj4+Hl9fX6XEh0qlIjQ0lAkTJpCeno6vr2+RXeJz584t9xyFEEIIIYQQQgghxPMhyWXxf9ajR48wGAxs376dqVOnKgfxXbhwARMTE/R6vbJ7GMDGxgYbGxtWr15NSEgIZ8+eNRrvnXfeYfjw4bzyyivKIX3379/n999/59GjRyQmJpKQkMBPP/3En3/+yZ9//smFCxfIyMhg7dq1ODs7U61aNdq0aVOmxO6dO3fYt28f9vb2Rs/HjRvHuHHjlPtjx44xePBg7t69+5e/VXk4OzvTq1evcsU0bNiQhg0bFtvm7e39LKYlhBBCCCGEEEIIIZ4zKYsh/s/68MMPmTBhAkOGDGHKlCkAHD16FBsbGzw9PdmyZUuRmJ9++ompU6eyYMECTE1Njdrq169Ply5djMpeHDhwgJkzZ7Jjxw5iYmLQaDS0aNGCESNGsHz5ctq3b8/UqVN5+PAhkZGRHDx4sNjE8q+//mp0bzAYSEhIYM2aNSxZsuQZfI0yykqH9GTISjN6HB0djbe3N/b29kyZMqVMhxyGhYXh6upKtWrV2LFjh1Hb6tWrqVKlCrVq1eLo0aNGbTNnzsTe3p4mTZpw+fLlv70kIYQQQgghhBBCCPHPkJ3L4v+kH3/8kfDwcFatWkVOTg6zZs0iOTmZ8ePHM3fuXOrVq0eHDh3w9PSkRYsWSkxAQABbtmyhZ8+eRcacPHkyOTk5+Pn5sXv3brp3787IkSMZOXJkifMoaYeywWDg3LlzZGdn07FjR6pXr87rr7+utGdlZdGwYUMePHhAeno66enpVKhQ4W9+lTK4FQmm+f8sWJiZ4WRjh06nw8/Pj27durFz504mTJjAli1bGD58eInDREdHM2jQIFavXs3LL79M3759ad68OfXq1SM8PJygoCB27txJpUqVGDx4MOfOncPR0ZH169ezfv169u3bR1JSEgMGDODSpUtKKQ0hhBBCCCGEEEII8eKQncvi/5z09HSGDh3K4sWLsbOzw8nJidmzZ9OzZ09atGjB66+/jqenJ5988gkdO3Zk2bJlpKamsnHjRpYtW0ZAQIAyVmpqqlEd4KlTpzJhwgRSUlLKNJe8vLxi6ybPnDmTiRMnMnfuXPbv38/PP/+Mubk5165dQ6/Xc+7cOXx8fNBoNKxfv14pHfH48WOysrLKtHM4JycHnU5XpnkWOP7RUiI+XUPEp2u4tnwzNStV5uDBg6SkpLB06VJq165NcHAwmzZtKnWckJAQOnToQGBgII0bN2b8+PGEhoYC+TWjhw4dir+/P61atcLf35/du3crbUFBQbRt25bevXtTr149Tpw4Ua41CCGEEEIIIYQQQojnQ3Yui/9zKlSowLFjx6hXrx4ADx48wNPTkz59+rBu3Tql3zvvvEPNmjV577336N+/P99++63SFhkZSZcuXXj06BEzZ840Gn/RokVlnktOTg6ZmZlFni9YsKDI4XXdunVj/vz52NnZKTWdIf+wwKVLlwLwxhtvcO7cOaM4g8GASqVSDvQrkJubS2BgIMuWLSvzfB1tbHmpVm2jZ5GRkfj4+GBlZQVAkyZNiImJKXWcyMhIevToody3bNmSjz76SGkrOFyxoO3EiROMHDmSqKgoNmzYYNQWERFB586dy7wGIYQQQgghhBBCCPF8SHJZ/J9UkFiG/APoLl68SI0aNYr06969OzExMUYH+wF4enqyfft26tati6ur61+ex65du4p9/mRiGaBWrVq0adNG2R1cnMOHDxd51qFDBwYMGMCoUaP+8jwLtJg6hutrtlGzUmXlmVarxd3d3WjuarWapKSkIocNlhRja2vLvXv3Sm1LS0tDr9cXabt+/frfXpcQQgghhBBCCCGEePakLIb4f0JxieUCTyaWC3Tp0uVvJZb/CoPBYDTX7Ozsp8ZYWFg8s5rEuuwcElONS35oNJoitaMtLCzIyMgocZwnYwr3L6lNo8n/XVdJcUIIIYQQQgghhBDixSLJZSH+RUePHqVPnz5KDWWtVoupqanSPmHCBMaMGaPcnz17lujoaKMx1Gp1kZ3Qv/76Kw8fPnwmc3RwcCAhIcHoWWpqaqkJ7SdjCvcvqc3S0hJLS8sS44QQQgghhBBCCCHEi0WSy0L8i44cOYK9vb2SHH706JFyCJ9Op+O7775j4MCBSv8lS5awffv2p447fPjwZ3YQnre3N2fOnFHuY2Nj0el0ODg4lDnm4sWLuLi4PLXNy8urxDYhhBBCCCGEEEII8WKR5LIQ/6LDhw/Tq1cv5f7GjRtKbeINGzZQuXJl2rVrp7RrNJoy7eQ1NTU12gH9JJ1Oh1arNbpK0q5dO7RaLZs3bwYgODiYzp07o1arSU5OJi8vr0hMv3792LlzJ1FRUaSlpbFixQq6desGQEBAAGvWrCE+Pp6HDx+yadMmo7ZFixah1Wq5fv06YWFhSpsQQgghhBBCCCGEeLFIclmIf8nt27e5fv06Xbt2BeDu3bskJSVx6tQpAB4/fsykSZOMYlQqVbGHAT7paX0WLlyInZ2dcpVWk1qj0RASEsL48eNxcnJi7969LFq0CAB7e3uioqKKxHh6ejJx4kS8vLxwcXFBrVYzduxYAPz8/OjUqRMeHh64u7vTrFkz+vbtC8CoUaOoXLky1atXp3HjxgwbNowWLVo8db1CCCGEEEIIIYQQ4vnT/NsTEOL/VTVr1uTx48eo1WoADh06hJeXF1euXCE2NpYPP/zwH3v39OnTmTx5snKv1WpLTTD37t2bGzduEBERgY+PD46OjgBKrejiLFiwgEGDBhEfH4+vr6+y41qlUhEaGsqECRNIT0/H19dXSYabm5tz+PBhTp8+jbm5OS1btnwWyxVCCCGEEEIIIYQQ/wBJLgvxLypILBsMBtauXctbb73F9evX+fDDD9m6des/9l5zc3PMzc3LFePs7GxUwqMsGjZsSMOGDYtt8/b2Lva5iYkJbdu2Ldd7hBBCCCGEEEIIIcTzJ2UxhHgBrF27luTkZAIDA5k1axY//vgj69ev/7enpYiOjsbb2xt7e3umTJlS6o7lAmFhYbi6ulKtWjV27Nhh1LZ69WqqVKlCrVq1OHr0qFHbzJkzsbe3p0mTJly+fPmZrkMIIYQQQgghhBBCPDuSXBbiX7Zt2zYmT57Mli1bqFChAlWrVuXbb7/lvffe44MPPiAzM1Ppm5OTU+Zxy5IAfpK5mSlONnZGz3Q6HX5+frRo0YLz588TExPDli1bSh0nOjqaQYMGMXv2bMLDw5kzZw7Xrl0DIDw8nKCgIDZs2MC2bdsIDAzk0aNHAKxfv57169ezb98+5s+fz4ABA8jOzi73OoQQQgghhBBCCCHEP09l+CsZKCHE3/bw4UNmzJjB9u3b2bJlCwMGDDBq/+WXX+jbty96vZ4RI0Ywbtw43n33XQ4cOICFhYXSLz09HVNTU6WmMUBqaipfffUVb7zxRpnmotVqsbOzI/rGH7xUq7ZR2549exgxYgR3797FysqKyMhIxo0bpxw8WJz33nuPq1evcujQIQCWL19OQkIC8+fPp0+fPjg7O7Nu3ToAJk2axEsvvURgYCBNmzZlwIABTJs2DYDXXnuNcePG0blz5zKtQwghhBBCCCGEEEL8fQW5opSUFGxtbUvsJzuXhfgX3L9/n+bNm3P69GlOnz5dJLEM4OPjQ3R0NAMHDuTkyZM4Ojqya9cusrKySE5OJikpieTkZHJycsjIyCA5OVm5Gjdu/Mx2/EZGRuLj44OVlRUATZo0ISYm5qkxHTt2VO5btmxJREREqW0Gg4GoqKgS44QQQgghhBBCCCHEi0WSy0IUY/78+cyaNavIcw8PD6Kjo4uNmThxIocPHwYgIyODx48fk5qaSlpamnIVlLioWrUqQ4cOZfHixbRo0QKAuLg4Dh48CICDgwPXrl3DwcGBzz//nJMnTxrtVgZo06YNx48fV+5jY2NRqVSkpaVx6dIlhgwZUu51t5g6htsJfxo902q1uLu7K/cqlQq1Wk1SUlKJ4zwZY2try71790ptS0tLQ6/XlxgnhBBCCCGEEEIIIV4sklwWopAmTZrQqFEjVq1axYYNG2jUqBHBwcE0b96cRo0acfv2bfr27UujRo3o37+/EhcbG8sXX3xBjRo1gPwD+lxcXKhWrRrVq1enevXqVKpUCT8/PyWmV69eDB06lPDwcCD/ALy1a9cCYGpqirm5OQaDodgdyJcuXSIhIYFWrVopz8zNzY3+96/QZeeQmJpi9Eyj0RQZ08LCgoyMjBLHeTKmcP+S2jQaTZH5P+09QgghhBBCCCGEEOLfI8llIQr55ZdfWLVqFX/++Sdvv/0227ZtIygoiFOnTuHv7092djbZ2dkcP36c7du3K3FLlixhxowZ1K9fn+TkZN5//30yMzNJTU1VSlVMmzbNqEZN69at2bt3L82aNQPyk8vnz5/Hzc2NxMRE2rRpg6urKw0bNiwyz2XLljFmzBjUajXp6ekASs1lU1PTZ/pNHBwcSEhIMHqWmppqVOP5aTGF+5fUZmlpiaWlZYlxQgghhBBCCCGEEOLFIsllIQrJysrinXfewc/Pj1u3bvHqq6/y888/c+7cOb755htcXFwYO3Ys/v7+ZGVlAfnlLI4dO8b7778PQO/evZk7d26RsVNTU5XkckJCAgkJCdSvXx8HBweOHTvGnTt3uHnzJnFxcVSqVIlTp05x+/Zt/vjjD6Nx7ty5w44dO7C3t+fy5ctGZSQKGAwGVCoVV69e/dvfxNvbmzNnzij3sbGx6HQ6HBwcyhxz8eJFXFxcntrm5eVVYpsQQgghhBBCCCGEeLFIclmI/3r48CG+vr4MGjSIFi1a4Orqyu7du7l16xaDBw/m66+/xsLCgt69e9OrVy98fHx49OgRY8aMYeHChZiZmXHgwAGioqIYNWpUkfELJ5enT59Onz59qF69OtHR0bRr145ff/21SF3l4nz44YdKqQxzc3MsLS2L9FGpVFhYWJS461en06HVao2ukrRr1w6tVsvmzZsBCA4OpnPnzqjVapKTk8nLyysS069fP3bu3ElUVBRpaWmsWLGCbt26ARAQEMCaNWuIj4/n4cOHbNq0yaht0aJFaLVarl+/TlhYmNImhBBCCCGEEEIIIV4smn97AkK8KCpXrsy8efPo27cv69evR6fT8cUXX9C5c2fCwsJo3rw5lpaWpKenM336dDp16sTly5c5dOgQMTExjB07lsTERD7//HOqVq1aZPzU1FQqVaoEQEhICABubm6YmZnRpk0bbt68iZmZGenp6SQlJeHt7Y2VlRXZ2dk0adKE8PBwfvrpJ/bt20eXLl2A/CSySqUqdj1qtRoTk+J/f7Rw4ULmzZtXpu+i0WgICQlh4MCBTJkyBRMTE44dOwaAvb09Fy9epGnTpkYxnp6eTJw4ES8vLywsLPDw8GDs2LEA+Pn58e233+Lh4QFAp06d6Nu3LwCjRo1i7969VK9eHZ1OR2BgoHLgoRBCCCGEEEIIIYR4sagMBoPh356EEC+i0NBQRowYwbVr16hVq1axfQwGA9u3b6dNmzbs3buXr7/+mtOnTxeb8PXz86Nt27Z88MEHyjM3NzcOHTpE/fr1Abh37x5NmzZFp9NRt25dzp07ZzTGvXv3OH36NN999x3du3fHx8eH7t27ExcXR2JiIpUqVaLgr7S1tTXR0dG4ubkVmYtOp0On0yn3Wq02/zDC3u2J+HwDzWt5FIl58OABERER+Pj44Ojo+PQPCMTExBAfH4+vr2+RXdTnzp0jPT0dX19fo++l1+s5ffo05ubmtGzZskzvEUIIIYQQQgghhBDPjlarxc7OjpSUFKMzxJ4kZTGEKMavv/7KmDFj8PDwoHfv3jRq1IhGjRrRoEEDVCoVe/bsAfJ3Dg8ePBhbW1sWLVrEhg0b+Oabbzh79myRMVNSUrCzsyvyPDU1lcTERCC/5MT48eOxtLQkNzeXAwcOGPWtVq0a/fv3/9vrMzc3x9bW1uh6GmdnZ3r16lXmxDJAw4YN6dKlS7HlOby9vWnfvn2RRLyJiQlt27aVxLIQQgghhBBCCCHEC06Sy0I8Yfv27XTt2pXg4GDmz5/P7t27iY6OJjo6mpEjR9K+fXv69OljFDNp0iRGjx5No0aNOHPmDLNmzSoybkm/6RkxYgSLFi3ixIkT/PDDD0yePBmAqVOnMnr0aG7cuPGPrLM8oqOj8fb2xt7enilTplCW/+AhLCwMV1dXqlWrxo4dO4zaVq9eTZUqVahVqxZHjx41aps5cyb29vY0adKEy5cvP9N1CCGEEEIIIYQQQohnR5LLQhSSm5vLTz/9xK5du5gwYQJarZZ27drxww8/sHv3bhYvXswXX3xhFLNs2TKio6N55513uHLlCk2bNuXw4cNcvHjRqN+ff/5ptOs3JyeHR48eUbFiRfr160e/fv3YsGED1tbWAPj4+DB69GiaN2/Op59+WqaELkBeXh7Jycll7l+YuZkpTjbGu6t1Oh1+fn60aNGC8+fPExMTw5YtW0odJzo6mkGDBjF79mzCw8OZM2cO165dAyA8PJygoCA2bNjAtm3bCAwM5NGjRwCsX7+e9evXs2/fPubPn8+AAQOUwwuFEEIIIYQQQgghxItFDvQTopCCw+sKDBs2TEmuuru7Ex4ejru7u9J+6tQpJk2aBECtWrWoX78+DRs2pHnz5qxevZrVq1dz5coVrl+/zoMHD2jQoIESe+7cOapVq8bYsWPp0qULs2fPVg7qK0gMz5gxA3t7e5KSkozKR+Tm5mIwGNDpdDx48AAvLy+Sk5MBsLOzw8HBgczMTPLy8sq1/ohFa6lZqbLRs4MHD5KSksLSpUuxsrIiODiYcePGMXz48BLHCQkJoUOHDgQGBgIwfvx4QkNDmT9/PmvXrmXo0KH4+/sD4O/vz+7duwkMDGTt2rUEBQXRtm1bADZv3syJEyfo3LlzudYhhBBCCCGEEEIIIf55klwWopALFy7wyy+/8PDhQ/744w8iIiJIS0tj7ty5TJ48WdlVXKB169Z8/vnn+Pr60rhxYzSa/L9SkZGR5ObmotFo6NevH3l5ecyZMyf/0Lz/atWqFVeuXAHy6wy/8cYbSptOpyMzMxOAMWPGFJnn1atXsbS0pFevXhw4cIBKlSrh6OiIo6Mj5ubmGAwG3Nzc0Ov15Vp/DadKRZ5FRkbi4+ODlZUVAE2aNCEmJqbUcSIjI+nRo4dy37JlSz766COl7c033zRqO3HiBCNHjiQqKooNGzYYtUVEREhyWQghhBBCCCGEEOIFJMllIQqxsbEhPDwcNzc32rZty+TJk2nWrBkmJsVXkFGpVMydOxdra2s0Gg1paWmo1Wru37+Pqamp0W7jjz/+GLVazZw5c2jfvj23bt2iQoUK3L59m7Fjx/Lnn3+yZMkSACpWrKgkZ9955x1mzJhh9N42bdpQpUoV5s2bx/79+zExMUGr1ZKbm4uDg4Oy89nDw6Nc67+TmMBLT9SF1mq1Rru1VSoVarWapKQk7O3tix3nyRhbW1vu3btXaltaWhp6vb5I2/Xr18u1BiGEEEIIIYQQQgjxfEjNZSEK8fDwYO/evSxfvpzRo0fTokWLEhPLBczMzDh16hRxcXEMHz4cPz8/TExMMDU15erVq+Tm5pKbm8tbb72FhYWFErNx40aio6OpWrUq/v7+ZGRk8OqrrxIXF6dcAwYMUHYwP3jwAHt7e7Kzs9FoNNjY2LB69Wpu375NXFwcc+bM4a233iIuLo5bt25x69atcq+/xdQx3E740+iZRqPB3Nzc6JmFhQUZGRkljvNkTOH+JbUV7PouKU4IIYQQQgghhBBCvFgkuSzE31Q4+XzkyBGllrCpqWmJfQv+99atWyQlJfHyyy+jVquLHb/guYWFBdnZ2ZiZmT3T+Remy84hMTXF6JmDgwMJCQlGz1JTU0udx5MxhfuX1GZpaYmlpWWJcUIIIYQQQgghhBDixSLJZSGekT///JPff/9dqQ9cUrK4sIMHD9KlS5en7o4uULjMBsD+/fuxs7PD2dmZOXPmsHnzZpydnXFwcGDq1KnlX0QxvL29OXPmjHIfGxuLTqfDwcGhzDEXL17ExcXlqW1eXl4ltgkhhBBCCCGEEEKIF4skl4V4Rg4dOkSXLl2wtLQEQK/XU79+fTQaDRqNhq1btxYb88orr/zld6rVapo1a8aDBw/46KOPGD58OA8ePGDChAlK3eXi6HQ6tFqt0VWSdu3aodVq2bx5MwDBwcF07twZtVpNcnIyeXl5RWL69evHzp07iYqKIi0tjRUrVtCtWzcAAgICWLNmDfHx8Tx8+JBNmzYZtS1atAitVsv169cJCwtT2oQQQgghhBBCCCHEi0WSy0I8Iw8fPqRChQrKfXZ2Njdu3DCqufykgIAAVq9eTXZ2NgBbt27Fzc1NudauXVvqO0vb8Vxa28KFC7Gzs1OuGjVqlNhXo9EQEhLC+PHjcXJyYu/evSxatAgAe3t7oqKiisR4enoyceJEvLy8cHFxQa1WM3bsWAD8/Pzo1KkTHh4euLu706xZM/r27QvAqFGjqFy5MtWrV6dx48YMGzaMFi1alPoNhBBCCCGEEEIIIcS/Q/NvT0CI/ysmTpxIw4YNOX/+PHXq1EGn06FSqcjKygIodofv4MGD+fbbb5VdzW+99RarVq1S2qdNm1bsu7Kzs7GysvrLc50+fTqTJ09W7rVabakJ5t69e3Pjxg0iIiLw8fHB0dERoNTd0QsWLGDQoEHEx8fj6+ur1E5WqVSEhoYyYcIE0tPT8fX1Vcp9mJubc/jwYU6fPo25uTktW7b8y2sUQgghhBBCCCGEEP8sSS4L8YyYmZkxcOBAvv32W958800AXF1djfp4enoWiWvXrh1nz56lbt26pY5vMBiUBPW9e/fo0qXLX56rubk55ubm5YpxdnamV69e5Ypp2LAhDRs2LLbN29u72OcmJia0bdu2XO8RQgghhBBCCCGEEM+flMUQ4hnQ6/XEx8fz+++/k5uby9GjR2natCkGg0G5hg4dahSj0+mYOHEiixYtKlPph6ysLHQ6HTqdjl9//RUfH59idw7/+eef3L17t0wHCpZFdHQ03t7e2NvbM2XKlFJ3KxcICwvD1dWVatWqsWPHDqO21atXU6VKFWrVqsXRo0eN2mbOnIm9vT1NmjTh8uXLz2T+QgghhBBCCCGEEOKfIcllIZ6RcePGYWtry8SJE1m+fDnDhg0rtb+5uTktWrRg7969jBo1CoAdO3bQqFEj5dq0aZPSv2rVquj1eubMmUPDhg2pUaMGubm5RcZdtWoVX331FR07diz3GszNTHGysVPudTodfn5+tGjRgvPnzxMTE8OWLVtKHSM6OppBgwYxe/ZswsPDmTNnDteuXQMgPDycoKAgNmzYwLZt2wgMDOTRo0cArF+/nvXr17Nv3z7mz5/PgAEDlFrUQgghhBBCCCGEEOLFI8llIf6mnJwcTExM2LNnDxs2bGD+/PmYmpoyevRoAFJSUoiJieHu3bvKIXsFSeG33nqLV155RXk2cOBAoqOjlWvkyJFGCdYvv/ySkJAQNm7cCED9+vUZM2aMMg+9Xs/7779PQkICnTp1KvdaIhatpWalysr9wYMHSUlJYenSpdSuXZvg4GCjhHdxQkJC6NChA4GBgTRu3Jjx48cTGhoKwNq1axk6dCj+/v60atUKf39/du/erbQFBQXRtm1bevfuTb169Thx4kS51yCEEEIIIYQQQgghng9JLgvxN+Xk5Cg/x8TEcPbsWT766CPOnj2rtLdu3ZrU1FS6d+9eJKZArVq18PX1NXrWq1cvunbtCsCZM2f48MMPCQ8Pp27dumRnZ1OlShXeeOMNIH+XcUpKCnZ2dlSoUOEvraWGUyWj+8jISHx8fJTDA5s0aUJMTEypY0RGRhrtmm7ZsiURERGlthkMBqKiokqME0IIIYQQQgghhBAvHkkuC/E3abVa3NzcgPwD7C5dukRsbCxz584F8mslv/rqq/z000/K4XbHjx+nc+fORuMsW7aM8+fPGz1r27Yt7du3B+CVV17hxo0beHl5ATBlyhS8vb2VshKzZs3i6tWrDB48mNTU1L+0ljuJCUXW5u7urtyrVCrUajVJSUkljvFkjK2tLffu3Su1LS0tDb1eX2KcEEIIIYQQQgghhHjxSHJZiH+AhYUFNWvWBKBSpUrcunWLkSNHlhoTEhLCqlWrOHToUIl91Go1BoOBDz/8kO+++479+/fj6OjIgwcPANi9eze3bt3C09OTkydPlnveLaaO4XbCn8q9RqPB3Ny8yNoyMjJKHOPJmML9S2rTaDQAJcYJIYQQQgghhBBCiBePJJeFeAays7MxGAzKfWZmJvb29kB+wvSbb75hxIgR5ObmkpKSAkBqaiqpqalkZWWRlZVFrVq1OHjwIG3btlWe6XQ6o/ekpKTg5+fHF198wfHjx6lbty737t2jTp06fPbZZ9SsWZNjx44xZMgQBgwYQHJycrnWocvOITE1Rbl3cHAgIcF4N3NqaipmZmYljvFkTOH+JbVZWlpiaWlZYpwQQgghhBBCCCGEePFIclmIZ6Bt27ZYW1vj5OSEk5MTH3/8MevXr8fCwoKKFSvSqFEjBg4cSMWKFXn55ZcBmDhxIpUrV1ZinJyc6NmzJ1WqVMHBwQFLS0scHByM3lOhQgV8/r/27jyq6mr///jzAHLAVAYJTUVB8zpPIYYjTjfzmlpqaTkbaQ45pak5lImo9dW85hDmeJ2TQqw0tVuWqDkQKohpOYtKDsABlAPC+f1hnp9HBkHpavp6rPVZ9fns4bP3ae0+a73dvre/P7t376ZSpUpYLBaGDh3K9evXrQf/2dvbM3nyZI4cOYKrq+t9zcvPz4/du3db70+ePInZbM42rrzaREVFUbZs2buW1a9fP9cyERERERERERF5+Ci4LFII9uzZQ2pqKpcvX+by5ctUr16dRYsWUbduXTZs2GB9npKSwq+//grAkiVLuH79OikpKTbXpUuXaNWqFdWrV2fXrl0273FwcGDChAmUK1cOgHfeeYeff/6ZPXv2sHjxYiZMmEBmZiZwM2dxbsxmMyaTyebKSbNmzTCZTCxduhSA4OBgWrdujb29PYmJidZ33a5z586sXbuW6OhoUlJSmDNnDm3atAGgS5cuzJ8/n7i4OOLj41m8eLFN2YwZMzCZTBw7dozQ0FBrmYiIiIiIiIiIPHwUXBYpZMnJyRw6dIiGDRvaPJ87dy4rVqzIs21CQgL//Oc/sVgs7Nmzhzp16uRar1u3bqxZs4atW7dSv359/vvf/7Ju3ToaN27Md999l+d7pk2bhouLi/Xy8vLKsZ6DgwOLFi1iyJAheHh4EB4ezowZMwBwc3MjOjo6W5s6deowbNgw6tevT9myZbG3t2fQoEEAtG/fnlatWlG5cmV8fHyoV68enTp1AmDAgAF4enpSrlw5atWqRZ8+ffD19c1zHiIiIiIiIiIi8uAYLLcnihWR+xYaGsrkyZOJjo7G39+f6dOnU7lyZapXr87KlStp3759ju3i4uJo06YNzz77LAsXLsTe3j5bnStXrrBw4ULmzJlDtWrVWLt2LZ6enjblgYGBbNiwgRo1avDSSy/xwQcfYDAYbPoxm802+ZxNJtPNAHOH5kR+vJBnKla2qX/x4kUiIyPx9/enZMmS+fodYmNjiYuLIyAgIFvu5H379pGamkpAQIDN2LKysti5cydGo5EGDRrk6z0iIiIiIiIiIlK4TCYTLi4uJCUl5fm34x3+h2MSeeRZLBY++ugjBg8ebH2WlZVFv3796N+/f66B5ZiYGNq2bUuPHj2YNm1arv1v376df//733To0IFFixbxj3/8I1udlJQUxo8fT0JCAo6OjtkCy3DzkEGj0ZjveZUuXZp27drluz5A9erVqV69eo5lfn5+OT63s7OjadOmBXqPiIiIiIiIiIg8GEqLIVKIZs2axfnz5+nVq5f1WXBwMCkpKQQHB+fYZuvWrTRt2pThw4fnGViGm/mMz549y4ABAyhTpgyJiYnZriZNmlC7dm3mzZvHxIkT73tOMTEx+Pn54ebmxujRo8nPX3YIDQ2lQoUKlClThjVr1tiUzZs3j1KlSlGxYkW+//57m7Lx48fj5uZG7dq1OXTo0H2PXURERERERERE/joKLosUkq+//ppx48axdOlSihYtSkJCAn/88QeJiYl89dVXFClSBIBz584BcP36dfr168fzzz/P008/TZ8+ffL1niJFimBnl/fSvVt5boyORfAo7mK9N5vNtG/fHl9fX/bv309sbCzLli3Ls4+YmBi6d+/OxIkT2bJlC5MmTeLo0aMAbNmyhVGjRrFw4UJWrlxJYGAgV65cASAkJISQkBA2btxIUFAQ3bp1Iz09/Z7mISIiIiIiIiIifz0Fl0UKwdKlS3n55ZeZM2cOjRs3ZsGCBdSoUYP4+HjGjh2Lu7s7AKmpqdSoUYOdO3fSqlUrTp48yYULF2jVqhXVqlWjb9++LF26lO3btxMZGcmhQ4fYsWMHX3/9tU2O5KysLM6fP4+rq2u2KyIigqysrHuaR+SMBZR/8v/ncN68eTNJSUnMmjWLSpUqERwczOLFi/PsY9GiRbRo0YLAwEBq1arFkCFDrAcZLliwgN69e9OxY0caNWpEx44dCQsLs5aNGjWKpk2b0qFDB6pUqcJPP/10T/MQEREREREREZG/noLLInexdetWDh8+nGv51atXWbZsGXPnzuXNN99kzZo1LFmyhHXr1tGrVy/69u2Lt7c33t7elC5dGj8/Pxo2bMiQIUPYsGEDpUqVYvr06ezdu5crV66wePFiAgMDadu2LU2aNOFf//oXM2fOtMmRfPXqVZu0GFevXuXo0aMkJCTQpEkT0tLS7mmuXh5P2twfPHgQf39/ihYtCkDt2rWJjY3Ns4+DBw/SsmVL632DBg2IjIzMs8xisRAdHZ1rOxERERERERERefjoQD+Ru/jss88oWbIkn376aY7l7u7u/PDDDwwYMACDwUC/fv3o168fgHUn8cSJE/n111+ZNGmStd1rr71m04+3tzd79uxhxYoVPPfcc3mOaf78+fTo0cN6b7FYKFOmDN988w0DBw6kfv369zTXs5cvUeO2E0BNJhM+Pj7We4PBgL29PQkJCbi5ueXYx51tSpQowfnz5/MsS0lJISsrK1vZsWPH7mkeIiIiIiIiIiLy19POZZHb9O3bl1KlSll3Gnt7e7Nr1y7CwsJsnnl5eVG5cmUADhw4wObNm4mPjyc2NpYvv/ySjIwMAIoVK4aLiwtdunQhKSmJkydP5vl+i8WCl5eX9T6nnMO//fYbe/bsYfTo0dZn9vb2eHh4ULZsWVJTU+nZs+c9zd93zEDOXPrDeu/g4GCzYxrAycmJa9eu5drHnW1ur59bmYPDzT/nyq2diIiIiIiIiIg8fBRcFrlNRkYGo0eP5tSpUyxfvpx//vOfnD59mvj4eF555RV69+7Nnj172LZtmzX1xOnTp/n555/5448/OH78OHv37iUiIoKGDRvSo0cPoqOjCQgIICIigvDwcJv3TZ8+nalTp1rvk5OTrQf/Afj6+rJy5UqbNmPGjGH69OmkpqbSq1cvTCYTcPOgP4PBwMsvv8ywYcOYPHlygedvTs/gcnKS9d7d3Z1Lly7Z1ElOTsbR0THXPu5sc3v93MqcnZ1xdnbOtZ2IiIiIiIiIiDx8FFwWuc2gQYOoWLEirVu3pkuXLtStW5fMzEwA+vTpw86dO6lQoQJff/0106dPB6Bjx45MmTIFf39/OnfuzPTp07G3t6dKlSrs2LGDJ598kh07drBnzx6GDx9u876NGzdSrlw54OZhf2lpadaD+yIjIzlz5gwdO3a01v/kk09ITEzklVdeYfr06dy4cYMffviBadOmkZiYSNu2bQkICGDTpk0YDAbrDup75efnx+7du633J0+exGw2Ww8ozE+bqKgoypYte9ey+vXr51omIiIiIiIiIiIPHwWXRW7j7+9PQEAANWvW5MiRIwwePNiaqqF69ep89913fPLJJ7Rr145XX30VgGvXrpGVlQXcTGtx/fp1a392dv9/iY0fP94mzUNCQgK//PILbdu2BeD3338HsOYnDg4Opnv37hQvXtzaJjw8nJiYGOrUqcMXX3zBvHnz+PbbbzEajZQvX56QkBB++eUXli9fzuDBgzlx4kSO8zSbzZhMJpsrJ82aNcNkMrF06VLrmFq3bo29vT2JiYnWwPvtOnfuzNq1a4mOjiYlJYU5c+bQpk0bALp06cL8+fOJi4sjPj6exYsX25TNmDEDk8nEsWPHCA0NtZaJiIiIiIiIiMjDR8FlkdvExsZSs2ZNFi1aRMWKFW3yLJcuXRpHR0emTp1Kq1atOHbsGNevX6dRo0b4+/uzefNmRo4cSZMmTTh9+rS1Tw8PDyIjI9m4cSNOTk7W51u2bKFevXp4enoCEB0dDUBERATp6elkZmYycOBAm/F9+eWX/PHHHwQEBDBr1izc3NxYsGABr732Gm5ubqxevZrXX3+dunXrUr16dT7//PMc5zlt2jRcXFys1+15nm/n4ODAokWLGDJkCB4eHoSHhzNjxgwA3NzcrGO+XZ06dRg2bBj169enbNmy2NvbM2jQIADat29Pq1atqFy5Mj4+PtSrV49OnToBMGDAADw9PSlXrhy1atWiT58++Pr65uu/m4iIiIiIiIiI/O8ZLBaL5UEPQuRhcuLECZ5//nnCwsKoUaOG9fn27dsZMmQIMTExNvUvXbqExWJh7969hIaGsmzZMiIiIli0aBFLliyhd+/eXLhwga5du/LGG2/YtM3MzMTe3h6AHj16cPHiRU6fPs3Ro0dtdj3fbtOmTfz73/9my5YtwM1UE2lpaTg4OODq6sro0aNxcnKiZs2a1sD1ncxmszX9BoDJZLoZYO7QnMiPF/JMxco29S9evEhkZCT+/v6ULFkyX79jbGwscXFxBAQEZMudvG/fPlJTUwkICMBgMFifZ2VlsXPnToxGIw0aNMjXe0REREREREREpHCZTCZcXFxISkqiRIkSudZTcFnkDi1btmTXrl24urri6OiIwWAgNTUVuLmwypQpw40bN0hKSuLy5cusXr2aX375hTZt2tCvXz+qVatGUFAQw4YNo3Tp0jz33HN88MEHnDt3DicnpxyDxhcvXqRSpUpERETQs2dPRo4cSb9+/bLV++abb+jSpQv+/v44OztTtWpVpk2bhtFoZMuWLcyaNYvVq1fTsGFDfH19Wb16tU3wNje3/oeRW3BZREREREREREQeH/kNListhsgdQkNDuXr1KhcvXiQ2NpZnn30WX19fli1bxj/+8Q9OnTrFuXPnSE5Oxmg0Eh8fj4ODAwD/+te/2Lp1K4cPHyYtLY2PPvqIzZs3YzQaiYqKonv37tneZ7FYGD58OO3bt6devXrMnj2bt99+m3379mWrW6lSJYKCghg5ciRBQUG8++671pzQTZo0Yc+ePTRu3JiAgABWrVqVr8Dy3cTExODn54ebmxujR48mP38eFRoaSoUKFShTpgxr1qyxKZs3bx6lSpWiYsWKfP/99zZl48ePx83Njdq1a3Po0KH7HruIiIiIiIiIiPx1FFwWuYO7uzuZmZnMnz+fatWqUbFiRb7++muKFSuWY/3Y2Fi++uor5s2bB4DRaKRXr17s2LGDoKAgWrRoQUhICAEBAVSpUsWm7Y0bN3jrrbfYsWOHtX3r1q0ZN24crVq1Yvny5TbB3IoVK/Liiy/i4ODAt99+S79+/fj1118BiIqKws7OjszMTBYuXEh6ejoJCQkFmrvRsQgexV2s92azmfbt2+Pr68v+/fuJjY1l2bJlefYRExND9+7dmThxIlu2bGHSpEkcPXoUuJlnetSoUSxcuJCVK1cSGBjIlStXAAgJCSEkJISNGzcSFBREt27dSE9PL9D4RURERERERETkf0fBZZE/Xb9+nY8++oguXbrg5eVFREQEmzdvZvr06Rw5coTdu3dnS2lx48YNdu7cyb59+/D29ub7779n6tSpREVFkZmZSe/evRk7diwdOnQgKirK5oC+gwcP0qxZMzZs2MC3335rk8v4nXfeYebMmfTv35+6desye/ZszGYz48aNo2bNmsydOxej0cjYsWMpXrw4w4cPp1OnTixYsAB7e3uCgoLYsGEDfn5++dppfEvkjAWUf/L/52nevHkzSUlJzJo1i0qVKhEcHMzixYvz7GPRokW0aNGCwMBAatWqxZAhQ1ixYgUACxYsoHfv3nTs2JFGjRrRsWNHwsLCrGWjRo2iadOmdOjQgSpVqvDTTz/le+wiIiIiIiIiIvK/peCyyJ+cnZ1JT0+nWbNmHD16lNWrV1OzZk0Ahg0bxoQJE3j++edt2vz666+0bNkSNzc3FixYwPbt27FYLEyePJkGDRrQtWtXnnjiCYxGI7Vr1+bNN98E4Pvvv8fX1xd3d3ciIyOpVatWtvG88cYbHDhwAG9vb44fP47RaOS9997j4sWLfPPNN7z99tsUK1aMevXqcfz4cSIjI+natSsjR45k+fLlvPrqqwwaNKhAqTG8PJ60uT948CD+/v4ULVoUgNq1axMbG5tnHwcPHqRly5bW+wYNGhAZGZlnmcViITo6Otd2IiIiIiIiIiLy8HF40AMQeZiMHz8egKCgINLS0ggKCgJg/fr1PPHEE9SuXZtevXpZg841a9YkJCQEuBmAfuGFF5gwYQLXrl0jLS2NIkWK2AR37e3tAQgICODHH3+kYcOGOR7wd0u1atX44osvuHHjBgCnTp2ia9eurF+/npo1a7J3716qVavGV199BcDp06cZOnQoMTExxMfH07hx4/v6PUwmEz4+PtZ7g8GAvb09CQkJuLm55atNiRIlOH/+fJ5lKSkpZGVlZSs7duzYfY1fRERERERERET+Ogoui9ymdu3aZGVlcfnyZbKystiwYQOvvfYaoaGhpKenc+bMGTp16oSjoyPVqlVj/fr12NnZcfLkSZYsWWJNe7FgwQImTJiAg4ODNaBsNptp3Lgx3333Hbt376ZXr144OTlhZ2fHjRs3OHXqFE8//TRXrlwhKyuLJ5+8uYs4KyuL5557jtmzZ1O7dm3eeustOnfuzOHDh+nXrx8nT54kLS0NJycnvv32W0qVKsXatWvJzMxk27ZtvP/++/me/8WEqzYngDo4OFgPDLzFycmJa9eu5RpcvrPNrfp5ld06EDG3diIiIiIiIiIi8vBRcFnkNj///DN79+6lZcuWjBs3jpdffpnq1aszfPhwpk6dSnBwMOnp6ezevZvixYtb282cOZN3332XqlWrkpiYyNtvv83bb79t0/fkyZM5ePAgAE2aNOHEiRPWsosXL9K6dWtiYmKYPXs2KSkpTJgwIccxDho0iJ49e+Ln50dSUhKurq588803tGzZksjISF577TW8vb3JyMgoUL5lgIuJCfyjgrf13t3dnZiYGJs6ycnJODo65tqHu7s7ly5dyrF+bmXOzs44Oztz6dIla3D7bu8REREREREREZEHSzmXRW6TlpZG//79ad++PadPn+aFF15g165d7Nu3j88//5yyZcsyaNAgOnbsSFpaGnAzVcX27dutweQOHTrkuFs4OTnZZlfwvTh58iQXLlygePHiREVF4eDgwJdffsmBAwfo1KkTJ06cYMqUKfTo0YO+ffvSr1+/+3qfn58fu3fvtnm/2WzG3d09322ioqIoW7bsXcvq16+fa5mIiIiIiIiIiDx8FFwW+VN8fDwBAQF0794dX19fKlSoQFhYGKdPn6ZHjx6sW7cOJycnOnToQLt27fD39+fKlSsMHDiQadOm4ejoyKZNm4iOjmbAgAHZ+r8zuHzq1CkcHBzw9vbGz8+PY8eO4e3tzQcffMDMmTPx9vamZMmSjB492trmVq7ltWvXApCZmWkt++677/Dx8aF06dJ4eHjg4eHBhx9+mONczWYzJpPJ5spJs2bNMJlMLF26FIDg4GBat26Nvb09iYmJNu+/pXPnzqxdu5bo6GhSUlKYM2cObdq0AaBLly7Mnz+fuLg44uPjWbx4sU3ZjBkzMJlMHDt2jNDQUGuZiIiIiIiIiIg8fBRcFvmTp6cnkydP5r333qNUqVKUKlWKJUuWUKxYMUJDQ3nmmWdwdnYmNTWVcePGsWzZMg4dOsS3337LkCFD8PLyonPnzkybNo2nnnoqW/93BpednJwoXbo0p06dYtOmTTRp0oRTp04xadIk3n77bU6dOsXUqVNtUkO88847bNiwgU2bNmGxWMjIyKBZs2Y4OzvToEEDvvvuO+Lj49m0aRNFixalWbNmOc512rRpuLi4WC8vL68c6zk4OLBo0SKGDBmCh4cH4eHhzJgxAwA3Nzeio6OztalTpw7Dhg2jfv36lC1bFnt7ewYNGgRA+/btadWqFZUrV8bHx4d69erRqVMnAAYMGICnpyflypWjVq1a9OnTB19f33z+1xMRERERERERkf815VwW+ZPBYLAJdK5YsYJFixYxevRoKlasCGATTG3QoAEWi4UVK1bQpEkTwsPDWbduXY67liF7cPnWIXYA+/bto3r16rmO63ZNmzaladOmACQmJnLx4kU6deqEs7OzNRDdpk0bNmzYgL+/f459jhs3jpEjR1rvTSZTrgHmDh06cPz4cSIjI/H396dkyZIAeeZznjp1Kt27dycuLo6AgADruAwGAytWrGDo0KGkpqYSEBBgnZ/RaGTbtm3s3LkTo9FIgwYNcu1fREREREREREQePAWXRXKwZ88eBg4cSOXKlenQoYP1eWZmJr/++ithYWG8+OKLGAwGevTowdWrV5kxYwZbt27l888/x8fHJ1twNCkpCRcXl2zvysrKYt68ecycORMAOzs7Tp48yd69e7ly5Uq2+mFhYWzfvp2ZM2diNpspWrQoAOnp6ZQvX57ixYtjMpkYMGAAaWlpHD9+HHt7e5s+jEYjRqMx379H6dKladeuXb7rA1SvXj3XgLmfn1+Oz+3s7KyBcxERERERERERebgpLYbIHVatWsVzzz1HcHAwQUFBhIWFERMTQ0xMDK+//jrNmzfnxRdftGkzYsQI3nzzTWrWrMnu3buZMGFCtn6TkpJyPNAvODiYMmXK0Lx5cwCeffZZIiIi6NKlC+fOnctW//vvv8fDw4PffvuNypUrW58bjUbOnDnD4cOHKV68ONu3b+fUqVPZAssFFRMTg5+fH25ubowePTrPHcu3hIaGUqFCBcqUKcOaNWtsyubNm0epUqWoWLEi33//vU3Z+PHjcXNzo3bt2hw6dOi+xi0iIiIiIiIiIn8tBZdFbnPjxg1++OEHvvzyS4YOHYrJZKJZs2Z88803hIWF8X//938sWbLEps3s2bOJiYmhf//+HD58mLp167Jt2zaioqJs6v3xxx/WlBK3GzVqFKtWrbLeP/vssxw9epQzZ85Qp06dbPU3bdrEyy+/zNatW3PdAXyvSru62dybzWbat2+Pr68v+/fvJzY2lmXLluXZR0xMDN27d2fixIls2bKFSZMmcfToUQC2bNnCqFGjWLhwIStXriQwMNC6OzskJISQkBA2btxIUFAQ3bp1Iz09vVDnJyIiIiIiIiIihUdpMURuc+sAu1v69OljDbD6+PiwZcsWfHx8rOURERGMGDECgIoVK1K1alWqV6/OM888w7x585g3bx6HDx/m2LFjXLx4kWrVqlnbZmZmEh8fT/369XMdT0JCAn369LF5n4ODAxUrVuSTTz5h/vz5AKSkpGBn9///rOjGjRv3NP/Sbu4295s3byYpKYlZs2ZRtGhRgoODGTx4MH379s21j0WLFtGiRQsCAwMBGDJkCCtWrCAoKIgFCxbQu3dvOnbsCEDHjh0JCwsjMDCQBQsWMGrUKGtajKVLl/LTTz/RunXre5qLiIiIiIiIiIj8tRRcFrnNL7/8ws8//0x8fDy///47kZGRpKSk8P777zNy5EiKFStmU79x48Z8/PHHBAQEUKtWLeshfQcPHuTGjRs4ODjQuXNnMjMzmTRpks2heWlpaZQqVYqYmJhcx/Ppp59y/Phxm/sWLVowe/ZsPD09adWqFTVr1sTNzY06deqwf/9+xowZg729Pe7u7rn2m18HDx7E39/fmte5du3axMbG3rVN27ZtrfcNGjTggw8+sJa99tprNmU//fQTr7/+OtHR0SxcuNCmLDIyUsFlEREREREREZGHlILLIrcpXrw4W7Zswdvbm6ZNmzJy5Ejq1auHnZ0dMTEx1KxZ06Z+ZmYmb731Vra8xrenszh58iRZWVnZdhN7eXlx+PBhm2e3Umfc6u/NN9+0KV+6dCkXLlygbNmy9OzZE3t7e6KioihSpAgAVapUoVu3bixbtgxHR8f7+zEAk8lks1PbYDBgb29PQkICbm5u+WpTokQJzp8/n2dZSkoKWVlZ2cqOHTt233MQEREREREREZG/hnIui9ymUqVK7Nmzh0mTJvHmm2/i6+uLnZ0d165do0WLFtbcwbcEBQXh4uKCi4sLrq6uFC1aFAcHB1xdXbNdL7zwgk3btLQ0/P392b17t/VZv379mDt3bq7jGzNmDKdPn8be3p6nnnqKIUOGsGnTJmv5zz//zPTp07PtsM6viwlXbe4dHBwwGo02z5ycnLh27VqufdzZ5vb6uZXd2vGdWzsREREREREREXn4KLgschs7OzuuXr2a7eC9okWLMnjw4Gw7ad9//31SUlJISkoiMTGRIUOG0L17dxITE20uk8nE1q1bbdp+8cUXXL16lerVq1t3NZ87d47GjRsDYLFYMJvNNm2aNWtGu3bt2Lx5MwC9evVixIgRpKWlAbB+/XpatGiR667iu7mYmGBz7+7uzqVLl2yeJScn57kr+s42t9fPrczZ2RlnZ+dc24mIiIiIiIiIyMNHwWWROzzxxBMAnD59GriZnsHd3Z25c+fSt29fPDw8MBgMJCTYBmItFgtffPFFvnIEZ2VlMX36dAYPHswXX3xBxYoVqVChAgcPHqRLly54e3vj4+ODj48PJpPJ2u7FF19kxYoVREdHAzfzEr/44ovExcVx/fp1wsLCmDhxYmH9FPj5+dnsrD558iRmsznPfM53tomKiqJs2bJ3Latfv36uZSIiIiIiIiIi8vBRcFnkT//61784ePAg9vb2fPPNNzRs2BCz2UyRIkX45ZdfuHz5svUCsu2qDQ8P5/z589nSX+Rk8eLFxMbG0qBBA/r168eZM2cIDw+nWrVqnDp1ynqdP3+eEiVKAJCeng5Ax44deeedd4CbOaJDQ0Np1aoV1apVw8nJCT8/P/r06ZPn+81mMyaTyebKSbNmzTCZTCxduhSA4OBgWrdujb29PYmJiWRmZmZr07lzZ9auXUt0dDQpKSnMmTOHNm3aANClSxfmz59PXFwc8fHxLF682KZsxowZmEwmjh07RmhoqLVMREREREREREQePjrQT+RP586do2TJkqSmphIYGMjq1asxGo3WfMB3uv0Qvxs3bjBhwgS6dOly15QUcXFxjB8/Hh8fH86ePUuZMmVwdHQkNTWV1NRUvL29berXqVOH8PBw+vXrx4YNG0hNTeXatWs4OztjZ2fHL7/8goeHh7X+smXL2LFjR55jmDZtGpMnT77LL3IzR/KiRYt49dVXGT16NHZ2dmzfvh0ANzc3oqKiqFu3brbxDhs2jPr16+Pk5ETlypUZNGgQAO3bt2f9+vVUrlwZgFatWtGpUycABgwYQHh4OOXKlcNsNhMYGIivr+9dxygiIiIiIiIiIg+GwWKxWB70IEQeBp6enkRHR/P0008TERFBnTp1APDw8GD//v02QV+DwcD169dxcnICYOzYscyYMQNXV1eboDNARkYGrq6u1jQbXbt2xd3dnSNHjvDOO+8QEBDAE088Qa9evWjYsCEDBw60ts3KysJsNuPs7Gx95uTkxPXr1zEYDBQvXpyTJ09mCy5HRESwaNGiXOdqNptt8jmbTCa8vLz48cAvNKtTL1v9ixcvEhkZib+/f7Z81LmJjY0lLi6OgICAbLu89+3bR2pqKgEBARgMBpv57ty5E6PRSIMGDfL1HhERERERERERKVwmkwkXFxeSkpKsf6s+J9q5LAJcuXIFDw8Pzpw5Q5UqVayBZYCUlBSaNm2aLWicnp6Ok5MTmzdv5sMPP8RgMLB7926qVq1qU2/79u288cYb1vthw4ZRsWJFunXrhp2dnTXHc0REhE1gGW4eMHh7YPmWWwHZtLQ0nnnmGezs/n+Gm5SUFP71r3/lOV+j0YjRaMyzzu1Kly5Nu3bt8l0foHr16lSvXj3HMj8/vxyf29nZ0bRp0wK9R0REREREREREHgzlXBYBSpYsSWxsLIcOHSIlJYU//vgDgPj4eMxmM0ePHrXJhfzbb79RrFgx1q9fT+fOnZk8eXKe6TBuT63RqFEjSpcubVMeFxdHQkICbdu2xdXVFVdXVwwGA8uWLctz3BkZGQwdOpS2bduyfft2HBwcuHz5Mv/5z3/u/ccQERERERERERHJBwWXRW7z3XffUbx4cerWrcv+/fs5duwYFSpUoGjRojb1nn76acLCwnjttdf44IMPmDhxYp793r6zOCdly5YlISGBxMREEhMT+fzzz/Hx8aFHjx451j9//jyvvPIK6enpHDhwINcdwoUhJiYGPz8/3NzcGD16NPnJpBMaGkqFChUoU6YMa9assSmbN28epUqVomLFinz//fc2ZePHj8fNzY3atWtz6NChQp2HiIiIiIiIiIgULgWXRf506dIlNm7cyBdffMHAgQMZMmQImzdvpnnz5jnWf/HFF9m5cyejRo0CyDPoente4dwsXLiQgQMHcuTIEaZMmcKECROyHSZosVjIzMykefPm1KlTh/T0dL766ivatm1rUy8xMZG4uLi7vvNOpV1td1+bzWbat2+Pr68v+/fvJzY29q67qWNiYujevTsTJ05ky5YtTJo0iaNHjwKwZcsWRo0axcKFC1m5ciWBgYFcuXIFgJCQEEJCQti4cSNBQUF069aN9PT0As9BRERERERERET+NxRcFvnTiBEjaNeuHeXLl2fixIl8/vnnLFu2jFdeeSXH+vb29jaHzmVlZdGwYUM8PDxsro4dO5KZmZmt/Y0bN2yed+nSBQ8PD/z9/dm9ezc1atTI1ubIkSNkZmYyfPhwxowZQ58+fWjSpAlPP/209ZDBzMxMtmzZQp06dfK1y/h2pd3cbe43b95MUlISs2bNolKlSgQHB7N48eI8+1i0aBEtWrQgMDCQWrVqMWTIEFasWAHAggUL6N27Nx07dqRRo0Z07NiRsLAwa9moUaNo2rQpHTp0oEqVKvz0008FGr+IiIiIiIiIiPzvKLgsAmzbto0vv/yS6dOnA7BmzRq6du2Kh4dHtl3Bublx4wa7d+/m8uXLNld4eDhpaWnZ6ptMJpudue7u7kyZMoXjx48zZMgQmjVrxo4dO2zaVK9enV9++YVGjRrRoEEDLly4wNixY1m6dCkeHh5kZWXh6OhIz549effdd/O1YzovBw8exN/f35oWpHbt2sTGxt61TcuWLa33DRo0IDIyMs8yi8VCdHR0ru1EREREREREROTh43D3KiKPvn/+85/ExMRQvnx5AJ599lmio6MJCwvDYDBw48YN/vOf//Dll19a23h5eTF37lwyMzMpUqQIR48epWbNmuzevZuqVatiMplwcXHBbDZz8uRJMjMzycjIwMnJCSDXnMIZGRn8+9//JjY2lmrVqmUrr1u3LmazmZEjR9K1a1e2bdtG//796dChAxcuXLiv3+FiwlVKlChhvTeZTPj4+FjvDQYD9vb2JCQk5HqA4Z1tSpQowfnz5/MsS0lJISsrK1vZsWPH7ms+IiIiIiIiIiLy11FwWeRPFStWpHXr1uzZswdHR0ccHR155ZVXSEtLo2/fvnh6emI0GhkxYgQffvghmZmZfP7554waNYrixYvj4OBAcnIyHTt2pEiRItaUFM888wxwM21GVlYWv/76KwcOHGD69Ol8+umnuLq62ozDaDQCNw8NvNOSJUt4++23cXFxAWDChAkAuLi4UK9ePZuDA81mMzVr1mTbtm35/g0uJibwjwre1nsHBwfreG5xcnLi2rVruQaX72xzq35eZbdyS+fWTkREREREREREHj5KiyFym++++45u3bpx8OBBrl69yuLFi6lRowbz5s2jePHiPPXUUzRp0oRz587x/PPP8+qrr3LixAkOHDhATEwMXl5ebNu2jY8++oglS5ZQp04doqKiiImJITY2ll9//RWASpUqERcXR+PGjTl//jwzZ8605miuXLkyAE899ZT12fr164GbB/rVqFGDU6dOcerUKUJCQjhx4gSXL1/mzJkzrFixgl9//ZVTp04xZcoUzGbzff0e7u7uXLp0yeZZcnIyjo6O+W5ze/3cypydnXF2ds61nYiIiIiIiIiIPHwUXBa5Q1xcHFOnTgXgv//9Lw0bNrSmgwBISkriyJEjtG7dGoA9e/bQtGlTPvvsM06ePImDgwM9e/bk5Zdf5saNG9SrV4+aNWsyf/586zuKFy/Opk2bcHJyIiwsjKysLF544QUuX77M8ePHAbh48SKXL1+mZs2a1naNGjVi7NixpKWl8frrr9OjRw/27NkDwLVr15gwYQLly5dn6tSpBAQEMHfu3BznaDabMZlMNldO/Pz82L17t/X+5MmTmM1m3N3dc6yfU5uoqCjKli1717L69evnWiYiIiIiIiIiIg8fBZdF/mSxWMjIyGDo0KGcOHECi8XChg0bGDBggM2BfD/88AONGze25iZu1KgRmzdvpkGDBqSmptKpUyeMRiNbt24lJiaGSZMmYTab6dWrl837ihcvzo8//sjgwYPvevDerfIqVaqQlZVF3bp1OXfuHIcOHSIzM5MxY8ZQtGhRgoODWbhwIZ9//jmNGjXKtuv4lmnTpuHi4mK9vLy8cqzXrFkzTCYTS5cuBSA4OJjWrVtjb29PYmIimZmZ2dp07tyZtWvXEh0dTUpKCnPmzKFNmzYAdOnShfnz5xMXF0d8fDyLFy+2KZsxYwYmk4ljx44RGhpqLRMRERERERERkYePgssifzp79iweHh706NGDyMhInnzyScxmM82bN6dcuXLWerGxsTg5OWGxWDhx4gTly5cnPDycOnXqEBgYSKNGjVi7di0vvPACkyZNYsSIEYSHh1OsWLFs73ziiScKNEaTycT//d//MXToUL799lueeuopzp49S2hoKFlZWYwePZr333+fdevWERQUhK+vb479jBs3jqSkJOt19uzZHOs5ODiwaNEihgwZgoeHB+Hh4cyYMQMANzc3oqOjs7WpU6cOw4YNo379+pQtWxZ7e3sGDRoEQPv27WnVqhWVK1fGx8eHevXq0alTJwAGDBiAp6cn5cqVo1atWvTp0yfX8YuIiIiIiIiIyIOnA/1E/lS+fHmSkpJyLZ89ezYAo0aNonnz5rz//vtMnjyZpUuX8t577/HSSy8REhKCo6MjP/74I56ensyePZuyZcvy9ddfc/bsWVxcXKhTpw7Ozs4AbNy4kQ0bNlCjRo18jbFIkSKEh4dTpEgRUlNTgZsBZ3d3d65du8bGjRsZPXo0V65coWvXrtZDBe9kNBqzHdSXmw4dOnD8+HEiIyPx9/enZMmSALn2DTB16lS6d+9OXFwcAQEB1tzJBoOBFStWMHToUFJTUwkICLDuyjYajWzbto2dO3diNBpp0KBBvsYnIiIiIiIiIiIPhsGSV4RI5DFz5coV6tata82vDDeDqKdPn2b27Nn8/vvvzJ07l99//52aNWty4sQJypQpw8aNGylRogTDhw/nxIkTBAQE8Oabb9K2bVv27t1LWFgYkZGRpKamEhERgb29PRaLBT8/P1q2bMmTTz7JxIkTKVasGBaLhatXr1qDuElJSaxatYpXXnmFd999l1mzZmE0Gq1B2WvXrpGRkYGzs7PNAXjp6elUrlyZgwcP3nXeJpMJFxcXfjzwC83q1CvkX1VERERERERERP5ObsWKkpKSrKlhc6Lgsshtrl69iqenJzdu3ADg8uXLlCtXjrS0NJvgckZGBmXLlmXlypW0bt2aatWq8emnn2IwGNi3bx/Lly/P1veYMWPo2bOn9f6zzz5j/Pjx/Pbbb2zfvp34+Hj69+9PQkIC7u7uZGRk4ODgwMKFC/H19c0xRURGRgZVq1alatWqnDx5kp07d+Lm5lbgeSu4LCIiIiIiIiIit+Q3uKycyyK3KVKkSLZnt+9ihptB4kqVKuHg4ICvry/r1q3D29ubFi1a0Lx5cywWC/Xr1ycmJsZ61a9fn5SUFGsfR48e5e2332bKlCm4uLjQsWNH+vfvn+OY+vfvn2vu4bFjx1K0aFE2btxIw4YNadOmDefPn7/n+Zd2LXhgWkREREREREREHk8KLovc5saNG2RmZlKuXDnKlStH7dq1yczMBLD+s23btkyZMoUjR47g6OjI6NGjGTt2bIHe89VXX/H000/zxhtvZCu79Z6srKxc258/f56+ffuyfv16QkNDsbe3Z+HChVSrVo1nnnmGkJAQ0tPTCzQmgNJu7gVuIyIiIiIiIiIijycFl0Vuk5WVRYUKFTh37hznzp3j8OHDlCpVCoC0tDQAmjdvTu/evXFxceHYsWP4+/vTokULax/Xr18nPDycmjVrWq/w8HDMZrO1zqhRo/jxxx+xs8u+BG8FhW+l5rhdREQE3bt3x8fHh0uXLrFr1y6qVKkC3NxhvXz5cmbOnMmkSZPw9PRk9OjRhffjiIiIiIiIiIiI3EY5l0UKWXp6OhaLBaPRWOh9Jycn88477/Dyyy/TsmXLXOtlZGSwefNmPDw8aNSo0V37zW8eHRERERERERERefTpQD8RyTcFl0VERERERERE5BYd6CciIiIiIiIiIiIifxkFl0VERERERERERESkwBRcFhEREREREREREZECU3BZRERERERERERERApMwWURERERERERERERKTAFl0VERERERERERESkwBRcFhEREREREREREZECU3BZRERERERERERERApMwWURERERERERERERKTAFl0VERERERERERESkwBRcFhEREREREREREZECU3BZRERERERERERERApMwWURERERERERERERKTAFl0VERERERERERESkwBRcFhEREREREREREZECU3BZRERERERERERERApMwWURERERERERERERKTAFl0VERERERERERESkwBRcFhEREREREREREZECU3BZRERERERERERERApMwWURERERERERERERKTAFl0VERERERERERESkwBRcFhEREREREREREZECU3BZRERERERERERERApMwWURERERERERERERKTAFl0VERERERERERESkwBRcFhEREREREREREZECU3BZRERERERERERERApMwWURERERERERERERKTCHBz0AEXnwLBYLACaT6QGPREREREREREREHrRbMaJbMaPcKLgsIly5cgUALy+vBzwSERERERERERF5WCQnJ+Pi4pJruYLLIoK7uzsAZ86cyfN/GCKSN5PJhJeXF2fPnqVEiRIPejgif0taRyKFQ2tJpHBoLYncP62jvyeLxUJycjJlypTJs56CyyKCnd3N9OsuLi76H71IIShRooTWksh90joSKRxaSyKFQ2tJ5P5pHf395GcDog70ExEREREREREREZECU3BZRERERERERERERApMwWURwWg08t5772E0Gh/0UET+1rSWRO6f1pFI4dBaEikcWksi90/r6NFmsFgslgc9CBERERERERERERH5e9HOZREREREREREREREpMAWXRURERERERERERKTAFFwWERERERERERERkQJTcFlERERERERERERECkzBZZFHVExMDH5+fri5uTF69Gjyc3ZnaGgoFSpUoEyZMqxZs8ambN68eZQqVYqKFSvy/fff/1XDFnnoFOZaslgsuLq6YjAYrFdQUNBfOXyRh8K9rCOAXbt2UaVKlWzP8/peiTzKCnst1a5d2+abFBgYWNhDFnno3Ms6mjx5Mu7u7hiNRl566SWSk5OtZfomyeOqsNeSvkl/XwouizyCzGYz7du3x9fXl/379xMbG8uyZcvybBMTE0P37t2ZOHEiW7ZsYdKkSRw9ehSALVu2MGrUKBYuXMjKlSsJDAzkypUr/4OZiDxYhb2WfvvtN1xdXUlISLBeo0eP/h/MROTBuZd1BBAZGclLL72E2Wy2eZ7XGhN5lBX2Wrp27RrHjx/njz/+sH6TPvnkk79o9CIPh3tZR6tWrWLVqlV8++23HD58mCNHjjB9+nRA3yR5fBX2WtI36W/OIiKPnLCwMIubm5slNTXVYrFYLAcOHLA0btw4zzbDhg2ztGnTxno/e/Zsy/jx4y0Wi8XSsWNHy4ABA6xlw4cPt3z22Wd/wchFHi6FvZZWrlxp6dat2183YJGH0L2so5SUFEv58uUtH3zwgaVChQo2ZXmtMZFHWWGvpYiICIu/v/9fNVyRh9K9rKNp06ZZdu3aZb2fNGmSpW3bthaLRd8keXwV9lrSN+nvTTuXRR5BBw8exN/fn6JFiwI3/3pJbGzsXdu0bNnSet+gQQMiIyPvWibyKCvstbR371727t2Lq6srnp6eTJgwId9/pVnk7+pe1lGRIkXYtWsXTZs2zbE/fZPkcVTYa2nv3r2cO3eOJ598EldXVwYOHJhtd7PIo+Ze1tHYsWNp2LCh9f7o0aNUrlzZ2p++SfI4Kuy1pG/S35uCyyKPIJPJhI+Pj/XeYDBgb29PQkJCvtuUKFGC8+fP37VM5FFW2Gvp2LFjtG/fnqioKFavXs2nn37KunXr/roJiDwE7mUdOTo6UrZs2Xz1p2+SPC4Key0dPXqUJk2aEBERwZYtW9i2bRsff/xxoY9b5GFyL+vodseOHSMsLIz+/fvn2J++SfK4KOy1pG/S35vDgx6AiBQ+BwcHjEajzTMnJyeuXbuGm5tbvtrcqn+3MpFHWWGvpc2bN1uf+/j4MHToUEJDQ+nWrdtfMHqRh8O9rKOC9KdvkjwuCnstffrppzb3kyZNYs6cOYwdO/a+xinyMLufdZSVlUW/fv0IDAykRo0aOfanb5I8Lgp7Lemb9PemncsijyB3d3cuXbpk8yw5ORlHR8d8t7m9fl5lIo+ywl5Ld/L09CQuLq5wBivykLqXdVSQ/vRNksdFYa+lO+mbJI+D+1lHU6ZM4erVq3z00Ue59qdvkjwuCnst3UnfpL8XBZdFHkF+fn7s3r3ben/y5EnMZjPu7u75bhMVFWX9a5R5lYk8ygpzLV2/fp1atWpx/fp1a9nu3bupUKHCXzN4kYfEvayjgvSnb5I8Lgp7LTVs2JCzZ89a7/VNksfBva6jr776ilmzZvHFF19Yc8zm1J++SfK4KOy1pG/S35uCyyKPoGbNmmEymVi6dCkAwcHBtG7dGnt7exITE8nMzMzWpnPnzqxdu5bo6GhSUlKYM2cObdq0AaBLly7Mnz+fuLg44uPjWbx4sbVM5FFWmGvJ2dmZUqVKMWjQIPbv38/HH3/M6tWrGThw4P96WiL/U/eyjvKS1/dK5FFW2GupRo0aDBgwgD179rB8+XJmzpypb5I88u5lHR05coRXX32VTz75BC8vL1JSUqypL/RNksdVYa8lfZP+5iwi8kgKDw+3FC1a1FKyZEnLk08+aTl8+LDFYrFYAEtUVFSObd59912Lo6OjpUSJEhZfX1/LtWvXLBaLxZKVlWXp0aOHxdnZ2eLs7Gx54YUXLFlZWf+rqYg8UIW5lk6fPm1p0aKFxWg0WqpUqWIJDQ39X01D5IG6l3VksVgsP/zwg6VChQrZnue2xkQedYW5lhISEiwvvviixdnZ2VKhQgXL/Pnz/8KRizw8CrqOhg8fbgFsrtvXk75J8rgqzLWkb9Lfm8FisVgeRFBbRP56Fy9eJDIyEn9/f0qWLJmvNrGxscTFxREQEJAtX9K+fftITU0lICAAg8HwVwxZ5KFU2GtJ5HF0L+soL1pj8rgq7LUk8jjSN0mkcOibJAAKLouIiIiIiIiIiIhIgSnnsoiIiIiIiIiIiIgUmILLIiIiIiIiIiIiIlJgCi6LiIiIiIiIiIiISIEpuCwiIiIiIiIiIiIiBabgsoiIiIiIiIiIiIgUmILLIiIiIiKSq+TkZF544QWKFi2Kp6cn+/bte9BDKlTLli2jefPmD3oYIiIiIn9LCi6LiIiIiEiuli1bxoULFzh+/Dg//vgj5cuXv+8+vb292b59+/0PrhC89tprfP311w96GAAYDAZOnTr1oIchIiIikm8OD3oAIiIiIiLy8Lpy5Qq1atXiqaee4qmnnnrQwyl0jo6OODo6PuhhiIiIiPwtaeeyiIiIiIhks3btWgwGA5MnT2b58uUYDAaqVq1qLd+3bx/PPvssLi4udOrUiaSkJGtZeHg4VapU4YknnqBVq1acP38egOeffx6DwcDp06dp0aIFBoOB6dOnA9nTU5w6dQqDwWC9b968OcuWLWPWrFlUqFCBTZs2Wcu+/fZbatWqhaurK4GBgZjN5nzPM6e0GAaDgbfeeotixYoRHBxM/fr1KVeuHKdPn6ZPnz5069YNX19f3N3dGTx4MBkZGda2oaGhVKlSBQ8PD4YMGUJaWpq1zNvbm++++45x48ZRunRpDh8+DEDVqlWtc/Xx8cFgMLB27Vpru88++4zy5ctTvHhxOnXqREpKCgDvv/8+ffr04YMPPsDV1RUfHx927txpbbdmzRoqV66Mi4sL3bp1s/lv9J///IfKlSvj4eHBu+++i8ViyfdvJiIiInKLgssiIiIiIpJN586dSUhIYMyYMbz66qskJCRY8y0nJibStm1b2rZty6FDhzCZTLz99tsAJCQk0LVrV8aNG8fvv/+Op6cnQUFBAHzxxRckJCTg5eXFV199RUJCAiNGjMj3mEJCQti2bRshISE8++yzAPz+++907NiRYcOGsW/fPvbu3ctHH3103/MvWrQoI0eO5P3332fu3Lk88cQTREREALBx40aCgoLYvn07W7ZsYe7cucDNgHvv3r2ZMWMGERER7N+/n7Fjx9r0O3HiRM6dO8eqVavw9va2tktISADg4MGDJCQk0LlzZwAOHz7MwIEDWbRoEbGxsVy5coX58+db+9u0aRMnTpwgKiqKxo0bM27cOAB27dpFYGAgM2fO5MCBA1y4cIH33nsPgJ9++onAwEBmzZrFf//7X5YvX86qVavu+zcTERGRx4/SYoiIiIiISDZFihTB1dUVJycnHB0dcXV1tZZ98803FClShPfeew+DwcCoUaPo1asXAMWKFeP06dO4uLiwf/9+UlNT+eOPPwB44oknALCzs6NYsWI2feZHSkoKP/74o00ai3Xr1lG3bl0CAwMBGDRoEEuWLGHChAn3MXvo27cvP//8M8888wz+/v489dRT1h3KnTp1om3btgAMHjyY8PBwRowYwaJFi+jevTsvvvgiADNnzuSf//wnH3/8sXVnsouLCytWrLB5V/Hixa3/XqJECZvfpVKlSly8eBEnJyf27NlDRkYGR48etZY7ODgQEhKC0WikV69eDBgwALi5I7tHjx506NABgIULF1p3kK9YsYKXXnqJ9u3bA9CzZ082btxIjx497us3ExERkcePgssiIiIiIlIg586d49KlS7i5uQGQlZVFcnIyaWlp2NnZMXbsWDZu3Ei1atUoXrw4mZmZBX7HtWvXsj178803s+VHPnfuHFFRUdaA7I0bNyhWrFjBJ3UHJycnm3/ezsvLy/rvZcuWJT4+HoCzZ8/SrFkza1mlSpW4fv06ly5dwtPTE4C33nqrQOO4fv06b7zxBjt27KBOnTrY29vb/J7+/v4YjUbgZv7oW+ktzp49a5Puo0qVKlSpUgW4+Zv98MMP1t8sPT2d2rVrF2hcIiIiIqDgsoiIiIiIFFC5cuXw9fVl3bp1AFgsFpKSkihSpAgrVqzg559/5vTp0xQrVoz58+fz+eef27S3s7PLluPXYDCQlZVlvY+MjMz23ls7n+8cS/v27Zk5cyYAmZmZOQamC9OpU6es/3727FlKly4NQPny5Tlx4oS17MSJEzg7O/Pkk09an+U0h1sMBkO23+Xf//43SUlJXLhwgSJFivDOO+9Yd4LDzZ3OOfHy8rIZ5w8//MCHH37I5s2bKVeuHAMGDLCmJMnIyLD57UVERETySzmXRURERESkQNq1a8eZM2fYu3cvzs7OhIaG8vzzz2OxWEhOTsZisXD16lU2b97MlClTsgVMK1WqxNatW7lw4QL//e9/gZs7gGNjYzGZTFy6dIkPP/wwX2Pp1q0bO3bs4LfffsNoNPLJJ5/Qt2/fQp/z7TZs2MCmTZs4dOgQ8+bNs+ZHDgwMZNWqVWzYsIGjR48ycuRIBgwYYHMwYV4qVarE5s2biYuL46effgIgOTmZrKwsLl26xOrVq1mwYEG+Dt/r27cvK1as4Ouvv+bkyZNMmzaN8uXLA9CrVy/Cw8O5ePEiDg4OjB8/nvHjx9/jryEiIiKPMwWXRURERESkQFxdXdm4cSMzZ86kYsWKrF+/no0bN+Lg4EDv3r3x9vamWrVqTJ48mQEDBnDkyBHS0tKs7T/66CO++eYbypcvz/vvvw9Ay5Ytee6556hVqxbt2rXj3XffzddYKlWqxH/+8x9GjhzJ008/zaFDh1izZs1fMW2rl19+mTFjxtCsWTPatWtnzXNcv359li9fzpgxY2jcuDG+vr5MmzYt3/0uWLCAmTNn4uPjQ0hICADDhw/HbDbzj3/8g6VLl/L6669z4MCBu/bVsGFDPvvsM0aMGMEzzzxD6dKlrQcdNm3alMmTJ9OzZ0+qVatGenq6zSGBIiIiIvllsOTnj71FRERERESEPn364O3tbQ2Ki4iIiDzOtHNZRERERERERERERApMO5dFREREREREREREpMC0c1lERERERERERERECkzBZREREREREREREREpMAWXRURERERERERERKTAFFwWERERERERERERkQJTcFlERERERERERERECkzBZREREREREREREREpMAWXRURERERERERERKTAFFwWERERERERERERkQL7f48bIbcMyC6QAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "dinglei=['部落冲突', '性别','是否不限量套餐到达用户','手机上网速度慢', '和平精英', '高铁','京东','阴阳师','梦幻诛仙','手机支付较慢', '打游戏延时大','优酷', '网络信号差/没有信号','客户星级标识',\n",
    " '咪咕视频','龙之谷','办公室','居民小区','看视频卡顿','其他，请注明.3','其他，请注明.1','地铁','搜狐视频','打开网页或APP图片慢','梦幻西游','农村', '淘宝',\n",
    " '腾讯视频','拼多多','显示有信号上不了网','是否5G网络客户','商业街','全部网页或APP都慢','芒果TV', '欢乐斗地主',\n",
    " '穿越火线','炉石传说','火山','全部都卡顿','抖音','今日头条','其他，请注明','上网过程中网络时断时续或时快时慢','百度','新浪微博','高校', '微信',\n",
    " '全部游戏都卡顿','其他，请注明.2','王者荣耀','下载速度慢','爱奇艺','其他，请注明.4','其他，请注明.5','快手','手机QQ']\n",
    "\n",
    "dingliang=['手机上网整体满意度', '网络覆盖与信号强度', '手机上网速度', '手机上网稳定性','套外流量费（元）', '套外流量（MB）', '脱网次数', '当月MOU', '微信质差次数', '上网质差次数',]\n",
    "# 重要性\n",
    "features_import = pd.DataFrame(X.columns, columns=['feature'])\n",
    "features_import['importance'] = DT.feature_importances_  # 默认按照gini计算特征重要性\n",
    "allcol=dinglei+dingliang\n",
    "def getcol(x):\n",
    "    for i in allcol:\n",
    "        if i in x:\n",
    "            return i\n",
    "\n",
    "features_import['feature']=features_import['feature'].apply(lambda x:getcol(x))\n",
    "features_import=features_import.groupby('feature').sum().reset_index(drop=False)\n",
    "features_import.sort_values('importance', inplace=True)\n",
    "# 绘图\n",
    "from matplotlib import pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 显示中文黑体\n",
    "# plt.rcParams['axes.unicode_minus'] = False # 负值显示\n",
    "fig, ax = plt.subplots(figsize=(15, 10))\n",
    "\n",
    "plt.barh(features_import['feature'], features_import['importance'], height=0.7, color='#008792', edgecolor='#005344') # 更多颜色可参见颜色大全\n",
    "plt.xlabel('feature importance') # x 轴\n",
    "plt.ylabel('features') # y轴\n",
    "plt.title('手机上网整体满意度 Feature Importances') # 标题\n",
    "for a,b in zip( features_import['importance'],features_import['feature']): # 添加数字标签\n",
    "    plt.text(a+0.001, b,'%.3f'%float(a)) # a+0.001代表标签位置在柱形图上方0.001处\n",
    "plt.savefig('./ans2/手机上网整体满意度featureimportance')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5b338f54-066a-4f0b-84ad-c81b6b9ab34f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 此处所引入的包大部分为下文机器学习算法\n",
    "import pandas as pd\n",
    "from numpy import *\n",
    "import numpy as np\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import learning_curve\n",
    "import xgboost as xgb\n",
    "import lightgbm as lgb\n",
    "from sklearn.metrics import accuracy_score,recall_score,f1_score\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "\n",
    "from random import sample\n",
    "from sklearn.model_selection import ShuffleSplit\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "from sklearn.model_selection import train_test_split\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "33f1581a-8993-4fb9-87d3-7bda0e87fc5e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple\n",
      "Requirement already satisfied: xgboost in e:\\runtimeenv\\python\\lib\\site-packages (1.6.2)\n",
      "Requirement already satisfied: numpy in e:\\runtimeenv\\python\\lib\\site-packages (from xgboost) (1.21.6)\n",
      "Requirement already satisfied: scipy in e:\\runtimeenv\\python\\lib\\site-packages (from xgboost) (1.7.3)\n",
      "\n",
      "[notice] A new release of pip available: 22.1.2 -> 23.0\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n",
      "Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple\n",
      "Requirement already satisfied: lightgbm in e:\\runtimeenv\\python\\lib\\site-packages (3.3.5)\n",
      "Requirement already satisfied: numpy in e:\\runtimeenv\\python\\lib\\site-packages (from lightgbm) (1.21.6)\n",
      "Requirement already satisfied: wheel in e:\\runtimeenv\\python\\lib\\site-packages (from lightgbm) (0.37.1)\n",
      "Requirement already satisfied: scikit-learn!=0.22.0 in e:\\runtimeenv\\python\\lib\\site-packages (from lightgbm) (1.0.2)\n",
      "Requirement already satisfied: scipy in e:\\runtimeenv\\python\\lib\\site-packages (from lightgbm) (1.7.3)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in e:\\runtimeenv\\python\\lib\\site-packages (from scikit-learn!=0.22.0->lightgbm) (3.1.0)\n",
      "Requirement already satisfied: joblib>=0.11 in e:\\runtimeenv\\python\\lib\\site-packages (from scikit-learn!=0.22.0->lightgbm) (1.2.0)\n",
      "\n",
      "[notice] A new release of pip available: 22.1.2 -> 23.0\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "!{sys.executable} -m pip install xgboost -i https://pypi.tuna.tsinghua.edu.cn/simple\n",
    "!{sys.executable} -m pip install lightgbm -i https://pypi.tuna.tsinghua.edu.cn/simple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "59b9fbc2-a820-4b4d-bf50-00a672e4f6aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "tr_x,te_x,tr_y,te_y=train_test_split(X,YY,test_size=0.3,random_state=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5279a98f-e186-4b35-a30c-1bd8b4fef16c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "神经网络:\n",
      "训练集准确度:0.441\n",
      "测试集准确度:0.435\n",
      "平均绝对误差: 1.8575498575498575\n",
      "ACC 0.4349477682811016\n",
      "REC 0.4349477682811016\n",
      "F-score 0.4349477682811016\n",
      "\n",
      "逻辑回归:\n",
      "训练集准确度:0.455\n",
      "测试集准确度:0.436\n",
      "平均绝对误差: 1.7317188983855651\n",
      "ACC 0.4358974358974359\n",
      "REC 0.4358974358974359\n",
      "F-score 0.4358974358974359\n",
      "\n",
      "决策树:\n",
      "训练集准确度:0.989\n",
      "测试集准确度:0.318\n",
      "平均绝对误差: 2.0489078822412155\n",
      "ACC 0.3176638176638177\n",
      "REC 0.3176638176638177\n",
      "F-score 0.3176638176638177\n",
      "\n",
      "随机森林:\n",
      "训练集准确度:0.904\n",
      "测试集准确度:0.407\n",
      "平均绝对误差: 1.7825261158594492\n",
      "ACC 0.4069325735992403\n",
      "REC 0.4069325735992403\n",
      "F-score 0.4069325735992403\n"
     ]
    }
   ],
   "source": [
    "model=MLPClassifier(hidden_layer_sizes=10,max_iter=1000).fit(tr_x,tr_y)\n",
    "print(\"神经网络:\")\n",
    "print(\"训练集准确度:{:.3f}\".format(model.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(model.score(te_x,te_y)))\n",
    "y_pred = model.predict(te_x)\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "# 准确率，召回率，F-score评价\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))\n",
    "\n",
    "\n",
    "print(\"\\n逻辑回归:\")\n",
    "logreg = LogisticRegression(C=1,solver='liblinear',multi_class ='auto')\n",
    "logreg.fit(tr_x, tr_y)\n",
    "score = logreg.score(tr_x, tr_y)\n",
    "score2 = logreg.score(te_x, te_y)\n",
    "print(\"训练集准确度:{:.3f}\".format(logreg.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(logreg.score(te_x,te_y)))\n",
    "y_pred = logreg.predict(te_x)\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))\n",
    "\n",
    "\n",
    "print(\"\\n决策树:\")\n",
    "tree=DecisionTreeClassifier(max_depth=50,random_state=0)\n",
    "tree.fit(tr_x,tr_y)\n",
    "y_pred = tree.predict(te_x)\n",
    "print(\"训练集准确度:{:.3f}\".format(tree.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(tree.score(te_x,te_y)))\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))\n",
    "\n",
    "print(\"\\n随机森林:\")\n",
    "rf=RandomForestClassifier(max_depth=20,n_estimators=1000,random_state=0)\n",
    "rf.fit(tr_x,tr_y)\n",
    "print(\"训练集准确度:{:.3f}\".format(rf.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(rf.score(te_x,te_y)))\n",
    "y_pred = rf.predict(te_x)\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1a84aba3",
   "metadata": {},
   "outputs": [],
   "source": [
    "Y1=traindata[traindata.columns[0]]\n",
    "Y2=traindata[traindata.columns[1]]\n",
    "Y3=traindata[traindata.columns[2]]\n",
    "Y4=traindata[traindata.columns[3]]\n",
    "X=traindata[setcols]\n",
    "test_X=testdata[setcols]\n",
    "YY=Y1\n",
    "tr_x,te_x,tr_y,te_y=train_test_split(X,YY,test_size=0.3,random_state=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "096141df-82f8-4d97-8602-f59cd5e5fc0e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "LGBM:\n",
      "训练集准确度:0.855\n",
      "测试集准确度:0.409\n",
      "平均绝对误差: 1.7454890788224122\n",
      "ACC 0.40883190883190884\n",
      "REC 0.40883190883190884\n",
      "F-score 0.40883190883190884\n",
      "\n",
      "LGBM:\n",
      "训练集准确度:0.845\n",
      "测试集准确度:0.406\n",
      "平均绝对误差: 1.7355175688509021\n",
      "ACC 0.40645773979107314\n",
      "REC 0.40645773979107314\n",
      "F-score 0.40645773979107314\n"
     ]
    }
   ],
   "source": [
    "tr_y,te_y=tr_y-1,te_y-1\n",
    "print(\"\\nLGBM:\")\n",
    "lgb_model=lgb.LGBMClassifier()\n",
    "lgb_model.fit(tr_x,tr_y)\n",
    "print(\"训练集准确度:{:.3f}\".format(lgb_model.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(lgb_model.score(te_x,te_y)))\n",
    "y_pred = lgb_model.predict(te_x)\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))\n",
    "\n",
    "\n",
    "print(\"\\nLGBM:\")\n",
    "xgb_model=xgb.XGBClassifier()\n",
    "xgb_model.fit(tr_x,tr_y)\n",
    "print(\"训练集准确度:{:.3f}\".format(xgb_model.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(xgb_model.score(te_x,te_y)))\n",
    "y_pred = xgb_model.predict(te_x)\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c2b5e944-18bd-41f7-be2e-18ed6c3c4a7b",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'E:\\\\RuntimeEnv\\\\Python\\\\lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 学习曲线函数\n",
    "\n",
    "def plot_learning_curve(estimator, title, X, y, ylim=None, cv=None,\n",
    "                        n_jobs=1, train_sizes=np.linspace(.1, 1.0, 5)):\n",
    "    plt.figure()\n",
    "    plt.title(title)\n",
    "    if ylim is not None:\n",
    "        plt.ylim(*ylim)\n",
    "    plt.xlabel(\"game num\")\n",
    "    plt.ylabel(\"score\")\n",
    "    train_sizes, train_scores, test_scores = learning_curve(\n",
    "        estimator, X, y, cv=cv, n_jobs=n_jobs, train_sizes=train_sizes)\n",
    "    train_scores_mean = np.mean(train_scores, axis=1)\n",
    "    train_scores_std = np.std(train_scores, axis=1)\n",
    "    test_scores_mean = np.mean(test_scores, axis=1)\n",
    "    test_scores_std = np.std(test_scores, axis=1)\n",
    "    plt.grid()\n",
    "\n",
    "    plt.fill_between(train_sizes, train_scores_mean - train_scores_std,\n",
    "                     train_scores_mean + train_scores_std, alpha=0.1,\n",
    "                     color=\"r\")\n",
    "    plt.fill_between(train_sizes, test_scores_mean - test_scores_std,\n",
    "                     test_scores_mean + test_scores_std, alpha=0.1, color=\"g\")\n",
    "    plt.plot(train_sizes, train_scores_mean, 'o-', color=\"r\",\n",
    "             label=\"Training score\")\n",
    "    plt.plot(train_sizes, test_scores_mean, 'o-', color=\"g\",\n",
    "             label=\"Cross-validation score\")\n",
    "    plt.savefig('./ans2/%s.jpg'%title)\n",
    "    plt.legend(loc=\"best\")\n",
    "    return plt\n",
    "\n",
    "cv = ShuffleSplit(n_splits=5, test_size=0.2, random_state=0)\n",
    "plot_learning_curve(logreg, \"逻辑回归\", tr_x, tr_y, ylim=None, cv=cv, n_jobs=1)\n",
    "plot_learning_curve(tree, \"决策树\", tr_x, tr_y, ylim=None, cv=None, n_jobs=1)\n",
    "plot_learning_curve(rf, \"随机森林\", tr_x, tr_y, ylim=None, cv=None, n_jobs=1)\n",
    "plot_learning_curve(model, \"BP模型\", tr_x, tr_y, ylim=None, cv=None, n_jobs=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6fe95636-3d0c-412e-9c82-f52ba43269cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'E:\\\\RuntimeEnv\\\\Python\\\\lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5q6yUAo5tCLpyRQo/DlqDLNu1a9LzybdzcupW57AwKeDIrULOwpDtfUFBzTsIeXA6LBFUKunfhMkk/bemQDNypGt/OI0c6fHPbFBQULV9e/fuxbp163D06FG0adMGO3bswKFDh1x6Pncnajg7TgiB7t27Y+7cuXj00Ufxxz/+EX369Kn1+a5evYq2bdvi+++/R0VFBWbOnIn58+dj+/btiIuLs/t++vrrr7Fs2TLs3LkTHTp0wJkzZyz3nTlzBgEBAYiKirLsc/SexcbGYubMmXjyyScBSAPmvW0qd0NrVi00tUlMTERiYmJTF0OaWbB1KzBvHpCfb90fGyuFmYaceSAHIPmXlp+f9MswNtb5MbYBSN70emsLkByGCgul4CNvctgpKgJKSqSfKyqkX8DysXXh6ysFILlF6EYAUoeGomNxMVT5+VKok8OQHIj8/Nx8s+pg2zbH52/VqkabOULksvr+4eRhpaWlAIDi4mKcPHkSCxYscKmVpTEcP34c3333HX744QeEhoYiLi7OpeMuX76MYcOG4ZNPPrG0lMhTiKdPn44RI0Zg7Nix6NGjB1566SXLd9GMGTMwdOhQjBkzBt26dcOCBQswc+bMWmcxTZ06FQ899BAmT56M2NhYPPXUUzCbzdi6dWs9au/dFBVompUJE4C77mqef+Gr1dX/+gsMlIJFx47VH2/bCmQy2QehsjJrK5AchuSWILlLzHaTg1BlJWAwAJcuSZsNDYAeAPDee47LHxAghZ+wMCngOOoikzfbIOTqNOBt26Qviqq/cM+fl/Zv3cpQQ03Pk3841dPo0aMxevRo9O3bF4mJiXj00UexaNEiXLp0CW3btvVoWTp37ow2bdpg6NChKCkpgY+PDx5++GG8/fbbNR7XtWtXvPbaa3j88cdRUFCAPn36WFakHzhwINauXYsnn3wShYWFGDduHF599VUAQP/+/fHuu+/i6aefxm+//Yb7778fL730Uq3lHDx4MJYsWYKHHnoIBQUFGD58ON555536vwFerEnXofEUnU6H0NBQ1+axe4DRaMSOHTswZswYZa7FUbUbrOpmMkljfa5csQYhm1Yg02+/4Xx+PmJNJqhLSqwhSB4f5K7gYGuLkNw1VjUMhYUBTzwhlcsRuSk/J6fRwqniz389eFPdKyoqkJOTg8TERMvaGvKg0FrH0NhqQV2jbtW/jtavX48tW7Zg3bp1CAwMxJEjRzBmzBhcunSpyX//e6L+zVVNdXf0b0VWl+9vttBQ3VXtBnMkIgKwXTDRJvCYDQZkfPUVYoYOhVqlsoYgg8E6PkhuBZK3q1etwcc2BJWUADeau1FaKm25ue7XTQhpoPVXXwEjRjTvMUDkHTQaoJ6XHfAmt912GzZt2oSePXuivLwc8fHxePnll5s8zFDjY6Ahz7DtBpNDQlBQ9W4ieZB0Td1gtgOkKyulcT7yoGjbIGQbeuT/5ua6NkV+3DigVy9pu+kmoG9foHdvqcwK/euYyBskJSXhq6++aupiUBNgoKHmybYVyJWuicTEmrvB5GD0zTfSOJnaGAzAoUPSJi8RoNVKY5B69gT69JFCzk03SWN4tFq25hARNSEGGmoZXOkGA4C77659OmzbtsCaNcDRo9J27Ji0lZRYf7adiRAXB3TvLoUcuTUnLk6a5cXWHCIij2CgIe/iynTYf/wDGD0aGD4cMBqlLq3r16WxNb/8Yg01x45J3Vd5edL23/9anysiAujWTeqykltyunQB/P0dBykiIqoXBhryPq5Oh72x+igAKYR06AAMGCCFHL1emtJ++TLw66/Wlpzjx4HTp6WxPD/8IG2ygACga1eou3VDfFgYVIGBUtBp1UrqVmNrDhGR2xhoyDvVdR0hlUoKHbbjeYSQQlDPnvYhp7QUyM6WQs7x49agU14OZGRAk5GBFMB6eYykJKBHD/sByFFR0mtxbA4RkUsYaMh71Xc6rLOQU1kpDR6+4w6pu6q8XNpOngSOHoXp+HH89r//ISo3F6qiImn/yZPAp59an6d9e6nLqmdPICVFCjnx8VKrEVtziIiqYaAhakhVQ05oqDXkxMcDQ4fCfO0a9h88iDGdO8PnwgVrd9WJE9LP+fnSoOXz54Evv7Q+d1iYFHK6d5emkPfrJ93295dacnx82JrTApnMJnyX+x0ull5ETHAMBncYDI268QLtb7/9hkceeQS7d+9Gjx49sG7duhZ30cT09HScPXvW4UWOa7qvLo9piLJQ3TDQEDW2qiFHvvJxfLy09e9v7a4yGqWFBeVBx3KX1alT0lo6+/dLm8zfH+jcWQo5PXpIXVY33SStmiy/JltzFGvb0W2Yt2se8nXWsV6xIbFYNXoVJnRrnEsfPPzww1CpVMjMzMTHH3+MCRMm4NixY9BqvePrYtGiRQ16kcizZ88iMTHR6bWtGvr1vJl3fEKJmiNn3VXt20sBxTbkXLsmteAcP24NOUePSl1ZR45Im0ytltblkUOO3JrTtq11XA5bc5q9bUe3YeKWiRCw/yI8rzuPiVsmYut9Wxs81Jw6dQo7d+7EhQsX0LZtW/zpT3/CK6+8gp9++gm33nprg75Wc1V16f2W9notmXddTIKoOZNbcgIDpa6qNm2ky0ckJEhTvkePBmbNAv72N+DDD4GffgI+/xx49VXg0UelQc2tW0uLCJ4+Ld338svAlCnS8d26SSsgL1worbNz4IB0na3SUutV1anRCCFw3XAd143Xpf/WsOkqdJi7c261MAPAsm/eznnQVehqfa7rhusuX/l6//79SEpKslxQUqPRYN68eZYv3WHDhmHjxo1Yvnw54uPjsWPHDsux3377LVJSUhAeHo4pU6aguLjYct/mzZuRmJiI4OBg3HvvvSgsLLTct2LFCrRr1w7BwcG4//77UVFRUWs5R44ciXXr1llu/+Mf/8D48eMtt1944QW0bdsW4eHhmDFjBkx1+Gynp6dj2rRpdvuMRiPmzp2L8PBw9O/fH+fOnbO739nr+fv7W67KrVKpoNFocODAgVpfDwBWr16NhIQExMTEID093dKKM23aNPz1r3/F7Nmz0apVK/Ts2RPHjx+vtV5CCDz11FOIiopCeHg4/vjHP1o+F5WVlXjmmWcQHR2N6OhoPPfcc5bjTCYTnn32WcTExCAhIQFvvvmm5b6zZ89CpVLhypUruO+++5CUlGT3nj311FOW47Zs2VJrGeuLLTREzV3VlhzAejXzDh2Am2+2tuTIVzg/ftw6JufoUemSDxcvStuePdbnCQ0Funa1DkDu3Vtq1QkKsrbksDWnQZQZyxDySsNcT0hAIL80H6GvhLr0+GuLryHIN6jWx124cAFt2rSx22f75QYAa9asQVhYGNasWYMBAwYAAPLy8jBmzBisWLECw4cPx/z58zFt2jR8+umnKC0txcMPP4z33nsPN998M2bNmoXly5fj5ZdfxrFjx5CWloY9e/YgJiYGkyZNwrvvvotx48ahe/fuDst45swZ3Hvvvdi1axdmzJgBANi5cyfuv/9+AMCOHTuwbNky7N27F2FhYRg7diw+/vhj3HfffS69V4689dZb+Pzzz7F3717k5uZi4sSJmDx5cq2vd+nSJZw7dw59+vRBUVERzGazS+Hy448/xpIlS7BlyxaEhITg/vvvR1hYGObPn285B4888giysrLwhz/8AX/729/w3nvv1fic//3vf7F27Vrs3bsXarUaY8aMwbhx4zBq1Ci8+uqr+Pjjj7Fr1y6YTCbccccduOmmm3D33Xdj5cqV2Lx5M/7zn/9Ap9PhvvvuQ7t27XD33XdbnnvChAm44447MG/ePMu+l156CVu3bsUXX3yBU6dOYdKkSfj555/Rq1evup8AFzHQECmRVitttiorpVAjTyWXQ47RKF3J/PhxaTbVsWPStPKTJ6XVj3/6Sdpkfn5Ap05SyOnRwzo2JzzcGnA4NqdFMhqN0NRyXq9du4ZvvvkGvjbrNP3zn//EoEGD8OijjwKQAkBsbCwKCgoQGhoKrVYLg8GAmJgYbN68Ga1atQIA+Pn5AQAMBgMSExPx043PoUqlwuHDhx2+flhYGO655x4888wzqKyshMlkwr59+/DBBx8AAIYOHYrc3FwIIbBv3z4AcKkFoyaffPIJZs+ejT59+qBPnz646667LPfV9HqhoaGWi2KGhYVZrjhdm3feeQfz58/HsBuzMNPT0/HCCy9YAk1cXBxeeuklAMCkSZOwefPmWp8zICAAgHSO+/btizNnzliuer1hwwYsWbIEKSkpAKRAFRERYSnLkiVL0LdvXwDAvHnz8Pbbb9sFmjFjxmDx4sV2r/f+++8jLS0NvXr1Qq9evXDTTTdh9+7dDDRE5AI55Nz4xQXAGnIMBiA5WQo5BoN1BeQzZ6xjc44elYLO9etAVpa0/etf0vOo1daur+7dpTVzeveWxvv4+bE1xwWBPoHQPa2DrlSHkOAQy5eJI9+e+xZjNo2p9Tl3TNmBIfFDXHptV4SFhdl1FQFA79698cwzz2DSpEkAgFmzZtmFGUBqobHtbmjfvj38/PyQm5uLm2++GR9++CGWLVuGOXPm4JZbbsGbb76Jjh07IjExEWvWrMHixYtx6tQpjB49Gq+//jqioqKQkJDgtJxt2rRBr169sG/fPuj1eqSmpiIsLAwAUFhYiGnTpiE7Oxv9+/eHv79/nbqcHLl48SI6dOhguZ2cnIyLFy822utVfT+Tk5ORm5truT106FDLz76+vi61+gwdOhRPPfUUpk+fjosXL+L3v/89XnvtNQQGBlZ7vcGDB9dYFjk8yubOnVvt9fLz85GWlmYJOmVlZUhNTa21nPXBQEPUktUUcoxG6ZpT8urHBoN0X36+tSXn2DFpJeQrV6Twc+YMsHOn9bmio6Uuq65drYsDJidL44DkgOOoNckLqVQqBPkGweRjQpBvUI2BZmTySMSGxOK87rzDcTQqqBAbEouRySMbdAp3SkoKjh8/jtLSUgQHB6OyshI5OTmIjY21PCYoqHrXVYcOHbDHpivzwoUL0Ov1iI+Px9WrV9G2bVt8//33KCsrwyOPPIInn3wSn3/+OS5cuID+/fvjwIEDKCkpwcSJE/HCCy/g9ddfr7Ws9957L3bu3AmDwYB7773Xsv+5555DXFwc9uzZA5VKVa+uJlmbNm1w4cIFy+3c3Fz43OgGru315PPs6jgmQHo/z5w5Y7l95swZxMfHW27LrT51cebMGUyYMAGLFy9GQUEBRo4cibfffhsLFixAXFwczp49i1tuuQUAsGzZMly7dg3PP/+8pSxyGKlaFsDxZyI2NhbPP/88Bg4cCAC4fv06VI38xw5/yxB5m9pCTrt2UjiRQ47ZLE0lP3XKPuScPQsUFEjb3r3W5woJkVpy5JDTs6c0tTw01NpNZTBwFeQaaNQarBq9ChO3TIQKKrtQo4L0nq0cvbLB16MZNGgQunXrhscffxzPP/883nnnHYSFhVm+6Jx54IEH8OKLL2Lt2rW4/fbbMX/+fNx9991o27Ytjh07hmHDhuGTTz5Bz549AUiDUAEgKysLDz30ELZt22b5kpTvq82ECRNw5513wmw223V3lJaWwt/fHwUFBfj444+xbds2dOvWzZ23w2L8+PFYvXo1hg8fjvPnz2Pbtm2WMTu1vV5MTAwCAwPx73//Gz179sSpU6cwfPjwGl/v0UcfxeOPP45bb70VISEheO655/DHP/6xXnX48ssvsXLlSnzwwQeW1iz5vf7DH/6A9PR0dO3aFZWVlXjjjTewbNkyS1nS09PRrVs36HQ6rFy5EmvXrq319aZOnYp3330X/fv3R2VlJSZOnIjp06eja9eu9apHTRhoiKh6yImMtA850dHSJRqGDZNum0xS19Tp09Zp5L/+KnVf6XTSDCrb2Ry+vkCnTtB06YKEyEiorl+XWnMiIqTXZGtONRO6TcDW+7Y6XIdm5eiVjbIOjVqtxvbt2zFjxgz07NkTvXv3xo4dOyytEc7ExcXhP//5D+bNm4e0tDTccccdeOuttwAAXbt2xWuvvYbHH38cBQUF6NmzJ/7f//t/AKTZSjNnzsTvf/97FBcXY9CgQfjLX/7iUlnbt2+PgIAABAQEIDIy0rL/r3/9Kx566CF07doVI0aMwKRJk5CRkeHmOyKZM2cOTp06hSFDhiApKclu/Ehtr+fj44N33nkHM2fOxNWrV/H444/XGmjuvfdeXLx4EVOnToXBYMDMmTMxZ86cetVh+vTpyMjIwKhRo1BeXo6RI0fiiSeeAAD86U9/gk6nw8iRI6HRaDB79mzLoOf58+ejpKQEd9xxB/z8/JCenm43hsiZRYsW4ZlnnsHgwYNhMpkwdepUPPLII/WqQ21Uoi7tYAql0+kQGhqKkpISt5rqGprRaMSOHTswZsyYWn9RtESsv4LrbxtyDAb7MTlms/Tfc+esISc7Wwo6165Vfy6VShqX07Wr1KIjd1m1bSt1WcmXeZCDjqMuGpPJ9etxeVhFRQVycnKQmJhomfYsDwoNCal5DI0tT68U3JjcqX9L4s31r6nujv6tyOry/c0/hYjIdY66q0wma6gxGKRWF7nLymyWtoIC4MQJmI4eReH+/WiTnw/V5ctATo602Y7LadNGmmElj83p2VMKPgEB1tYcrRb497+BBQuqXzF91SrrFdNbAI1ag2EJw5q6GETNHgMNEdWPRmMNG7KqISc0FEhMhHnoUPw4YgTGJCXBp7TUuvJxdrY0qyonB7h8Wdq++cb6fK1aWQNO165St9arr0qrK9s6fx6YOFGanWUzUJSIWj4GGiJqeM5CTnm5NO4mKkq62GabNkBqqnSfWi1NJT91yjqNPCtL+vnaNeDgQWmriRBSV9acOdI1suQFAuVNo+FgZKIWioGGiDxDo5HWrAGkSzT4+EhBRh6To9dLgSckRBpLI4ccs1la6Vgek7NvnxR2nBFCGlNz++1S11X79lJXVHy81HXVtq0UtOSrlDdy2PGCYYpE9dJQ/0YYaIio6Wg00ubvL10hHHAccrp0kWZZjRwp/fzUU7U/96lT0laVn58UcGJjpbATFyddQiIhQfpvWJj0GNtZV26EHXnFXYPBYFmllYiqKysrA4B6T5JgoCGi5qW2kNO5s2vP8+ST0nPk5kozr3JzpTE2er3U7XX6tOPjoqKsgSc2Vgo58fHSFhcnPacLYUer1SIwMBBXrlyBj48P1Go1zGYzDAYDKioqvG6WCwDW34vr76juQgiUlZXh8uXLCAsLq/WyG7VhoCGi5s825Nx5pxQ0zp+vPigYkIJF27bAH/4g/SyPq9FopO6rS5ekmVHnzwN5edawc+6cNNj4yhVpc7R2ib+/tQtLDjtyy05ystS6cyPsqDQaxERFIScvz3J1ZiEEysvLERAQ0OirpjZHrL/31r+muoeFhSE6Orrer8FAQ0TKotFIU7MnTrQGFpn8i3LVKqBjR6llp7LSOutKr5fCR/v20j6z2XqsWi0NPj5/3j7wnD1rbd2pqHC9dadDB/h26IBOCQkwJCcD0dEwqtX4NicHQ1JT4ePr63UDlI1GI7799lsMGTJEeWswNQBvrr+zuvv4+NS7ZUbGQENEyjNhArB1KzBvXvV1aFaurHkdGrNZCjPyZht4goKkdXS6d68eeMxmaTq5bdjJzbW27pSWOmzdUQPwBwB/f/i1a4e+rVsjsEsXaORurKQk6ermISH2XVgtMOxoNBpUVlbC39/f677QAe+uvyfqzkBDRMo0YQJw1111XylYrZY2Z79UqwYeOfTI6+kkJEiPqay0Bh4hpEBz4YK1hScvz9qldeECUFEB1ZkziDlzxv6yELI2baRAJg9Stg077dtL5W3BYYeovhhoiEi5NBrp+lINqT6Bp317ICWleuAxGoGCAlSeP49fDx5ET5MJmvx8a+vOtWvWBQX/97/qr+nvXz3sJCZK3WrJydLCg7ZT0Bl2yAsx0BAR1UVtgUcIazeWbeCJjobo0gVnIyPRvUsXaADpPiGAkhKpZefCBalVJz9f2nJzLa07TqehA9IgaHmQcocO1rDTqZN0YVHbWVkMO9RCMdAQETUklcp6Uc2qjEbgyBGphUWlsg89HTtKg5bla2DJ+41Ga1eWvMlhJzdXat25dEnaDh2q/poBAfatO0lJUqtOx45S8LFt3WHYIQVjoCEi8jSttuYWHtvByiaTFIDkWVq2gaeyEigutg5Ulgcry2N4LlyQFiY8eVLaHGnbVgo78iBlOewkJ0vjkuSxO162bgopDwMNEVFzolJZW0wccRR45KubV1TYB57ycinU2AYeOezk5gLXr1tbdxxdJysgwH7cTnKyNfAkJUmzwuobdkymug/sJnKAgYaISElcDTxy6ElOtnZd6fVSS488aLmwUAo3tmvvyIHn4kUpEJ04IW2OyiG37iQkWLuykpKkwBMTI5WxprCzbZvjqferVtU89Z7IAQYaIqKWxDbwyBcDtWUbeDp0APr0cRx4ysutU8/lQcq243fKyoCCAmlzNA09MNAadhITgaQkqOLj0aqwUBr389VXwH33VV/t+fx5adHErVsZaqhOGGiIiLxJXQKP3LojBx6DQdrk1p2zZ60tOrZjeAoKpMBz/Li03aAFMByAmD1barlxdOkK+VIV8+dL6wyx+4lcxEBDRERWrgae+HhpzR15LI9t4Ckrsy4qKAee/HyI/HyYcnOhraiwX4XZ0Wvk5QE33wz07St1Y91o5UHHjtI1szhImapokkCTlZWF6dOn49SpU5gxYwaWLVtW44W6jEYjnnnmGXz00UcwGo149NFH8eyzz0LrrA+ZiIgah6tjeDp1sh+8bDSisrwcOzIyMPbwYWiXLKn9tf73P8cLDYaHWy8MKo/fkcfwJCRICxFyCrrX8Xgi0Ov1GDduHEaNGoUPP/wQc+fOxcaNGzF9+nSnxyxZsgQ7d+7Erl27oNfrMXHiRAgh8MILL3iw5EREVKuaAo/RCBw+DAwc6NpzTZ0qPY88dic/X1qEsKhI2jIzqx+jVksDkm2vlSW37iQnA+3aOQ9jpGgeP6s7d+5ESUkJli9fjsDAQCxduhSzZ8+uMdC89957WLFiBbp37w4AWLhwId5++20GGiIiBRJDh0qzmc6fdzyORqWSLiPxxhvSbfnSEnq9FGTOnZM2ecCy7dR0vd46nmffvurPLS80GB9vbd1JTLROSWd3lmJ5PNBkZmYiNTUVgYGBAIDevXsjOzu7xmMKCwvRoUMHy22NRlPj5cb1ej30er3ltk6nAyB1XRmNxvoUv0HIZWgOZWkKrL/31t+b6w6w/pb6m81QvfYaNJMmASoVVDahRtzoKjK99hpEQED1J4mOlrqzbBcXlANPeTlw6RJUN8buqPLyoLoRdlTnz0v31bLQoAgPh7hxCQmRmAhxY5aWSE6WurkCAtzuzvLm8+9u3evyeJUQjuJx41m4cCEqKiqwevVqy76oqCicOHEC4eHhDo/53e9+h2HDhuHFF1+EyWTC0KFDMWjQICxbtszh49PT07HEQf/spk2bLEGKiIiaVsz+/ei1bh0CfvvNsq8sMhJZjzyCi652S9WB2mhEwJUrCLx0CUGXLiHwxhZ06RICL1+Gb2lpjceb1WqUR0airG1blLVpg7LoaFy/8d+ytm2hDw3l2J0GVlZWhilTpqCkpAQhISE1Ptbjgebpp5+G0WjE8uXLLfvi4uLw448/on379g6PyczMxJ133olu3brh9OnTyM3NxYkTJ5CYmOjw8Y5aaOLi4lBYWFjrG+IJRqMRu3fvxogRI+DjbPnzFoz19976e3PdAdbfYf1NJqi+/96yUrD43e8ab6q2fOFQeWFBeUq6vP5OcTFw9qzUsnPj0hGq/HxrK4/BUPPT3+jOEh06SC07CQkQSUkQN7q1jEFB2P3VV155/t397Ot0OkRGRroUaDze5RQREYGsrCy7faWlpfD19XV6TJ8+fXD27FkcO3YMDz30EKZPn+40zACAn58f/BxMN/Tx8WlWH6LmVh5PY/29t/7eXHeA9berv48PcPvtnnvxGr5rYDIBvXpVm50FvV66rERBgbSo4Llz9qsrnz8PFBRYurNUTrqztBERGNK6Nfy7dYNaHqgsb/LsrBY+fqeun/26PNbjgWbAgAFYu3at5XZOTg70ej0iIiJqPE6j0aCsrAzHjx/Hv//978YuJhEReRuNxnnrkBBS6BgwwBp2bAcrX78uBRx5sHLVy0mUlEB19SrCr151PH5Ho5FmZ8XFSYOUExKkQcpy8JFnZ7FLyymPB5ohQ4ZAp9Nhw4YNmD59OpYuXYrbb78dGo0GxcXFCA4Odjrg99lnn8XChQvRrl07D5eaiIi8Wm0LDprN0mBl264sebFBvR4oLobxzBlkHDiAfpWV0Mizs+TAYzBYp6bv31/9+avOzpJnZsn/DQvz+lWVPR5otFot1q1bh8mTJyMtLQ1qtRp79+4FAISHhyMjIwMpKSnVjvvmm29w+PBh/Otf//JsgYmIiGqjVkubsy4Skwno3BkXtVqYhwyBBrDvzrp0SbqUhDwV3fbq6JcuSTO4apidhYgI67WzbBcbTEqSQlBAQON0ZzWjq6U3yepC48ePx+nTp3Ho0CGkpqaidevWAICaxicPHToUFy9e9FQRiYiIGo5GYx2/06qVffARQmpp6d/ffvyOXi9tVS8lUTXwlJQAV69Km6PFBuXurA4dpHBjO34nOVmaCu/jU/furGZ2tfQmWy4xOjoaY8eObaqXJyIiah5qu5yE2Sxdw8o27FRWSi07NrOzkJtbfezO+fP23Vl1WWxQDjyhoVIosg0827ZJV0VvRldL5/rPREREzZla7Xx2lnztrB497MfvyGN39HppdpbtysrudGfdWGzQ0oX14ovN7mrpDDRERERK5cpg5aqzs2yvjH79uhR0cnNr7846fNi1MslXS//uO2DYsAasbM0YaIiIiFoqVwYr287Oqqy0DzzytbPkwHP+PJCRARw/Xvtre3jcKwMNERGRt5LX3nHUpSWE1M3Uo4e1K6uyEti7F7j33tqfOyamwYtbEwYaIiIiqs7ZYOW77qr9aumxsdIUbg9q2WssExERUcPSaKSp2UD1qd7y7ZUrPb4eDQMNERER1c2ECdLU7KoXlY6NbZIp2wC7nIiIiMgdEyZI3U/evFIwERERtQAajUenZteEXU5ERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeE0SaLKysjBgwACEh4cjLS0NQogaHy+EwOOPP46IiAiEhYVh2rRpKC8v91BpiYiIqLnzeKDR6/UYN24c+vXrh4MHDyI7OxsbN26s8Zj3338fx48fR0ZGBr777jv8+uuveOmllzxTYCIiImr2PB5odu7ciZKSEixfvhzJyclYunQp1q9fX+MxP//8MyZOnIj4+Hj06tULd999N06dOuWhEhMREVFzp/X0C2ZmZiI1NRWBgYEAgN69eyM7O7vGY3r06IH3338f9957LyoqKvDhhx9iwYIFTh+v1+uh1+stt3U6HQDAaDTCaDQ2QC3qRy5DcyhLU2D9vbf+3lx3gPVn/b23/u7WvS6PV4naBrA0sIULF6KiogKrV6+27IuKisKJEycQHh7u8Bij0Yh+/frhl19+AQCMGzcOn376KdRqxw1M6enpWLJkSbX9mzZtsgQpIiIiat7KysowZcoUlJSUICQkpMbHeryFRqvVws/Pz26fv78/ysrKnAaaVatWISwsDOfOnYNKpcLMmTORlpaG1157zeHjFy9ebNeCo9PpEBcXh5EjR9b6hniC0WjE7t27MWLECPj4+DR1cTyO9ffe+ntz3QHWn/X33vq7W3e5h8UVHg80ERERyMrKsttXWloKX19fp8d88MEHeP7559GhQwcAwEsvvYShQ4c6DTR+fn7VQhMA+Pj4NKsPUXMrj6ex/t5bf2+uO8D6s/7eW/+61r0uj/X4oOABAwZg//79lts5OTnQ6/WIiIhweozZbMbly5cttwsKCmAymRq1nERERKQcHm+hGTJkCHQ6HTZs2IDp06dj6dKluP3226HRaFBcXIzg4GBoNBq7YwYPHoyXX34ZGo0GBoMBr7zyCsaPH+/pohMREVEz1SRjaNatW4fJkycjLS0NarUae/fuBQCEh4cjIyMDKSkpdse8+OKL0Ol0eOqpp1BaWopRo0Zh1apVni46ERERNVMeDzQAMH78eJw+fRqHDh1CamoqWrduDQBOVwwOCwvDe++958kiEhERkYI0SaABgOjoaIwdO7apXp6IiIhaEF6ckoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSvSQJNVlYWBgwYgPDwcKSlpUEIUePjp02bBpVKVW07e/asZwpMREREzZrHA41er8e4cePQr18/HDx4ENnZ2di4cWONx7z55psoKiqybDt27ECnTp0QFxfnmUITERFRs+bxQLNz506UlJRg+fLlSE5OxtKlS7F+/foajwkMDERYWJhlW7FiBdLT06HRaDxUaiIiImrOtJ5+wczMTKSmpiIwMBAA0Lt3b2RnZ7t8/IEDB5CTk4NJkyY5fYxer4der7fc1ul0AACj0Qij0ehmyRuOXIbmUJamwPp7b/29ue4A68/6e2/93a17XR6vErUNYGlgCxcuREVFBVavXm3ZFxUVhRMnTiA8PLzW46dOnYqUlBQsWLDA6WPS09OxZMmSavs3bdpkCVJERETUvJWVlWHKlCkoKSlBSEhIjY91K9AYjUa8+uqr+Oyzz5Cfn48vvvgC06dPx+bNm5GcnFzjsU8//TSMRiOWL19u2RcXF4cff/wR7du3r/HYq1evIjExEWfPnq0x/DhqoYmLi0NhYWGtb4gnGI1G7N69GyNGjICPj09TF8fjWH/vrb831x1g/Vl/762/u3XX6XSIjIx0KdC41eX0xBNP4MCBA3j88ceRlpaGwMBADBo0CDNnzsSXX35Z47ERERHIysqy21daWgpfX99aX3fbtm0YPHhwrS05fn5+8PPzq7bfx8enWX2Imlt5PI319976e3PdAdaf9ffe+te17nV5rFuDgrdu3YqPP/4YM2fOhEajgUajwdNPP42ffvqp1mMHDBiA/fv3W27n5ORAr9cjIiKi1mO3bNmCCRMmuFNkIiIiasHcCjRxcXH49ttvLbdVKhV+/fVXJCYm1nrskCFDoNPpsGHDBgDA0qVLcfvtt0Oj0aC4uBgmk8nhceXl5fjmm28wbNgwd4pMRERELZhbXU7Lli3D3XffjXfeeQdlZWVYsGABvvvuO7z33nu1v6BWi3Xr1mHy5MlIS0uDWq3G3r17AQDh4eHIyMhASkpKteP27duH8PBwJCUluVNkIiIiasHcCjSjR49GVlYWtmzZgptuugmxsbF45ZVXXA4b48ePx+nTp3Ho0CGkpqaidevWAFDjisHDhw9HQUGBO8UlIiKiFs7tdWg6duyIZ555xu0Xjo6OxtixY90+noiIiEjm1hiaXbt2oaioqKHLQkREROQWtwLNrFmzcPDgwYYuCxEREZFb3Ao0c+fOxcqVK1FZWdnQ5SEiIiKqM7fG0LRu3RpFRUXo168fZs2ahaCgIMt9U6dObbDCEREREbnCrUCzceNGy2q8W7ZssexXqVQMNERERORxbgWar7/+uqHLQUREROQ2t8bQyC5fvoyDBw+isLCwocpDREREVGduBZqSkhLcc889iI6OxuDBg9G2bVtMnDgROp2uoctHREREVCu3As3s2bNhNpuRn5+P8vJy5OXlobKyEk888URDl4+IiIioVm6Nodm5cycOHTqEdu3aAQDatWuHFStWoF+/fg1aOCIiIiJXuNVC06FDB+zZs8du3549exAfH98ghSIiIiKqC7daaFatWoWxY8diy5YtSEpKwpkzZ7Bv3z785z//aejyEREREdXKrRaaIUOGIDs7G8OGDYNKpcJtt92G7OxsDB48uKHLR0RERFQrt6+2HRcXh0WLFjVkWYiIiIjc4lYLzfnz5zFhwgTs2LEDANC3b1+MGTMGBQUFDVo4IiIiIle4FWgee+wx+Pr6IiUlBQDw4YcfIioqCrNmzWrIshERERG5xK0up++++w5Hjx61TNvu3Lkz/va3v6Fnz54NWjgiIiIiV7jVQpOYmIgvv/zSbh+nbRMREVFTcauFZvny5Rg/fjw+/PBDJCUlIScnB99++y22b9/e0OUjIiIiqpVbLTTDhw/Hr7/+iiFDhkAIgSFDhuDXX3/F//3f/zV0+YiIiIhq5VagOX36NP785z8jLS0Njz76KDZv3oyxY8fihx9+aOjyEREREdXKrUDz8MMPIygoCBqNBgsWLMC4ceMwfvx4XpySiIiImoRbY2gyMjLw0Ucfoby8HIcPH8ZXX32FgoICrFq1qqHLR0RERFQrtwJNQkICPvroIxgMBgwYMABqtRp79+7lLCciIiJqEm5fnPKhhx5CYGAg/vnPf+Lbb7/FI488gg8++KChy0dERERUK7cCze23346LFy9abpeXl+Py5csIDg5usIIRERERucrti1PaCggIaIinISIiInKLW7OciIiIiJoTBhoiIiJSPAYaIiIiUjwGGiIiIlI8BhoiIiJSPAYaIiIiUjwGGiIiIlI8BhoiIiJSPAYaIiIiUjwGGiIiIlI8BhoiIiJSPAYaIiIiUjwGGiIiIlK8Jgk0WVlZGDBgAMLDw5GWlgYhhEvHmc1mDBo0CK+99lojl5CIiIiUxOOBRq/XY9y4cejXrx8OHjyI7OxsbNy40aVj3377bZSUlGDu3LmNW0giIiJSFI8Hmp07d6KkpATLly9HcnIyli5divXr19d63IULF/DMM8/gjTfegI+PjwdKSkREREqh9fQLZmZmIjU1FYGBgQCA3r17Izs7u9bj5s+fj/j4eOTl5WHfvn0YNGiQ08fq9Xro9XrLbZ1OBwAwGo0wGo31rEH9yWVoDmVpCqy/99bfm+sOsP6sv/fW39261+XxKuHqAJYGsnDhQlRUVGD16tWWfVFRUThx4gTCw8MdHrN//34MGjQIY8aMQb9+/bB582aMGjUK//jHPxw+Pj09HUuWLKm2f9OmTZYgRURERM1bWVkZpkyZgpKSEoSEhNT4WI8HmqeffhpGoxHLly+37IuLi8OPP/6I9u3bOzzmD3/4A7Kzs7F//36oVCrk5eUhPj4eR48eRZcuXao93lELTVxcHAoLC2t9QzzBaDRi9+7dGDFihFd2n7H+3lt/b647wPqz/t5bf3frrtPpEBkZ6VKg8XiXU0REBLKysuz2lZaWwtfX1+kx+fn5GDNmDFQqFQApAEVFReH06dMOA42fnx/8/Pyq7ffx8WlWH6LmVh5PY/29t/7eXHeA9Wf9vbf+da17XR7r8UHBAwYMwP79+y23c3JyoNfrERER4fSY2NhYlJeXW25fu3YNV69eddqiQ0RERN7F44FmyJAh0Ol02LBhAwBg6dKluP3226HRaFBcXAyTyVTtmMmTJ2Pt2rX46quvcO7cOTzxxBPo2rUrevfu7eniExERUTPk8S4nrVaLdevWYfLkyUhLS4NarcbevXsBAOHh4cjIyEBKSordMSNGjMArr7yCxx9/HHl5eUhJScHWrVstXVBERETk3TweaABg/PjxOH36NA4dOoTU1FS0bt0aAGpcMfiRRx7BI4884qkiEhERkYI0SaABgOjoaIwdO7apXp6IiIhaEF6ckoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSvSQJNVlYWBgwYgPDwcKSlpUEIUesxvXv3hkqlsmwzZszwQEmJiIhICTweaPR6PcaNG4d+/frh4MGDyM7OxsaNG2s8pqysDKdPn8bly5dRVFSEoqIivPHGG54pMBERETV7Hg80O3fuRElJCZYvX47k5GQsXboU69evr/GYjIwM9O7dG1FRUQgLC0NYWBgCAgI8VGIiIiJq7rSefsHMzEykpqYiMDAQgNSVlJ2dXeMxP//8M/Lz8xEVFQWj0YjJkydj5cqV8PPzc/h4vV4PvV5vua3T6QAARqMRRqOxgWriPrkMzaEsTYH19976e3PdAdaf9ffe+rtb97o8XiVcGcDSgBYuXIiKigqsXr3asi8qKgonTpxAeHi4w2NmzZqFkpISpKeno7i4GA888ABmzJiBRYsWOXx8eno6lixZUm3/pk2bLEGKiIiImreysjJMmTIFJSUlCAkJqfGxHg80Tz/9NIxGI5YvX27ZFxcXhx9//BHt27d36Tnee+89vP766zh48KDD+x210MTFxaGwsLDWN8QTjEYjdu/ejREjRsDHx6epi+NxrL/31t+b6w6w/qy/99bf3brrdDpERka6FGg83uUUERGBrKwsu32lpaXw9fV1+TnatGmD8+fPO73fz8/PYXeUj49Ps/oQNbfyeBrr77319+a6A6w/6++99a9r3evyWI8PCh4wYAD2799vuZ2TkwO9Xo+IiAinxwwcOBB5eXmW2/v370d8fHyjlpOIiIiUw+OBZsiQIdDpdNiwYQMAYOnSpbj99tuh0WhQXFwMk8lU7ZgePXpg5syZ+Omnn/Duu+/itddew+OPP+7pohMREVEz5fEuJ61Wi3Xr1mHy5MlIS0uDWq3G3r17AQDh4eHIyMhASkqK3TF///vfMX36dNx2221o06YNXn31VTz88MOeLjoRERE1Ux4PNAAwfvx4nD59GocOHUJqaipat24NAE5XDA4LC8Mnn3ziySISERGRgjRJoAGA6OhojB07tqlenoiIiFoQXpySiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUT9vUBSAiIiJlEkLALMwQENCoNFCpVE1WFgYaIiIiL2IWZgghICAc/iwHFNufzWYzTMIEkzDZ/SyEsBwfFRSFMP+wJqsXAw0REVEzVlP4qOnnSnNltSBihtkuhFQ91hmVSgUVVFCr1HY/m8wmHLx4EHkleegW1Q1jO42FRq3x4LtjxUBDRETUwByFDGOlEQBQZiiDRmiqPUYOHCazCSazCWaYUWmuhBDC6XPK/1NB6uqx/VmluhFAoHL8c5V98n9dtePkDjz79bO4eO2iZV9sSCxWjV6FCd0mNNRb6TIGGiIi8nqWcGDbzeJCK4ht+LD92bYVRH7OyspKAEBuSS7UWnW1IOIsfMj/1aq01VpImmrMyo6TO/DY549BQNjtP687j4lbJmLrfVs9HmoYaIiISJGcjfdwOg7ESSuIyWyydLc4O9YZZ60gAKBRa+zCh1kjvUZYQBg02qbplmkIJrMJz379rMP3RQ5p83fNx11d7vJo9xMDDRERuUzu/rD9MnN1n9zloq/Uw6QyVXtcTQNSK82VMMNs97OjVhDLzzA77IYB4LCVwzaQWFpCGroVxPkQlSZlMptQaiiFTq+z20r0JdLPFdLPpYZS6Cp0yC3JtetmqkpAIE+Xh+9yv8OwhGEeq0eTBJqsrCxMnz4dp06dwowZM7Bs2TKXPzDFxcXo1q0b9u/fj4SEhMYtKBGRDfnLF7B+Uddln9zlIH+h1/f5nO2zDRFms9myT95fn322r1v1fakt0FQapfqfLT5raaGo+jhH40GcDUgFALVa7bSrxltUmiurB5EKHUoNpZaf7QJKla3UUNoo5bpY6jz0NAaPBxq9Xo9x48Zh1KhR+PDDDzF37lxs3LgR06dPd+n4tLQ0FBQUNHIpiagp2f7V7epYBvk4wPEXutnmz+Oq++S/9GvbZ/sajm7XFDaA6l/oDo+t0ppQ330ALF/utvfVZ1/V++RwUdtzmFXS+9jKtxW0Plq7x3lTAKnKYDI4bh25EUR0Bp3DUFKiL0GpvhTXjdcbpBz+Wn+E+oUixC8EIX4h1p/9QxDiG2L5ueBaAVb+uLLW54sJjmmQcrnK44Fm586dKCkpwfLlyxEYGIilS5di9uzZLgWab7/9Ftu3b0fr1q09UFIicpXDmRcOug/kLocSfQnUlWqH4xnqMrXUZDbh0MVDKCwrRGRgJPrF9INGrbH7Yrf9omyIfZbbKutjagoAts8hf6EH+wVbWii86QvdpJa6mTRqjSUEmcwm/HT+J1y+fhltgtrglva3NNm0X3dVVFZYQ0ZFibVlRG8fREoqSpB/MR+qApUUUm7sr6isaJByBPkEWYJIsF9wtVAS6heKYN9gy8+2wSXYLxi+Gl+XXsdkNuGjrI9QcK3A4TgaFVSIDYnF4A6DG6RervJ4oMnMzERqaioCAwMBAL1790Z2dnatx+n1esycOROvv/46nn766Vofq9frLbd1Oh0AwGg0wmg01qP0DUMuQ3MoS1Ng/Zu+/lXDhsMWEVQPJvKaFraDK22nlToKMbZMJukL7XzReag1akAFp10Ktvu0Kq102+a+nad2Iv3bdLu+/JhWMUgfko47Ot7hsfeymqq/321v33g7hElAqKq3JrV0pkqT3X+bwzkUQqCissIaQAzVu2Qc7rvRVaPT66A36Wt/IVtOeniCfYMtIUNuEbELJnIriZ/Nfb7WQKJV1+MrXVjPiyvSh6Rj1o5ZUEFl9xmWA/rfb/87zCYzzCbpQ+/u7726PF4lHHWINqKFCxeioqICq1evtuyLiorCiRMnEB4e7vS45557DocPH8Znn32GhIQE7N271+kYmvT0dCxZsqTa/k2bNlmCFBEp1/7i/Xjl7CtO73864WkMDBvowRJRXTXUORRCoMJcgWumaygzleG66brDrab7THD9i9wZFVQI0gQhUBOIIE1QtS1Q7Xi/vAVoAqBRKatlan/xfqw7vw6/GX+z7Iv0icQj7R9psH9/ZWVlmDJlCkpKShASElLjYz3eQqPVauHn52e3z9/fH2VlZU4DzdGjR/H2228jIyPDpddYvHgxFixYYLmt0+kQFxeHkSNH1vqGeILRaMTu3bsxYsQI+Pj4NHVxPK6l199Rl4v0/xvdLkYjvt/7PQYOGwiNRmP3WMtqnrY/1zKbo+q4CbvbKlRbz0Ju6ne01kVjr2thqjQhc18m+gzq4/a0VZPZhMc3Pu70fhVUeK/wPcy6c1az67poiPo3FdvPHwC7z5/t/VUfb/uzqdKEX376BV37d8XMLTNrfL01F9fAL84P1wzXamw5KdWXwiTqH0g0Ko1964dvsF23jG3LSbBflft8QxDkG2Q3lsgRJZ9/R/qiLx4zPYafz/+McyXn0DmyM+5IvsPhvzt3f+/LPSyu8HigiYiIQFZWlt2+0tJS+Po67rsTQuCxxx7Diy++iHbt2rn0Gn5+ftVCEwD4+Pg0qy/Q5lYeT2su9a9tsGlNU0kdjf+Qf7k6e15zpdQEe+n6Jai09uMvqk0h1aihhrrafVUfpzQarabGX+gms8nSBVBSUSKNP7gxBuGXS7/UOmX04rWLGLV5FIJ9gy377Abg2n7Z1vIlXfWYql/SVY+Vf5ZDbNX7Ksor4Hva13EQENVnFNX0es5eo8awUdfXaAy/1P6QYn0xnv/ueZef0kftYz+Y1d++68bZuBH550CfQI/9W6rt898U5N9ttpvt7y95X1UqqJDSLgV92/dFm1Zt4O/nX+Pr1PX3fl0e6/FAM2DAAKxdu9ZyOycnB3q9HhEREQ4fn5ubi++//x6//PIL0tLSAEiJrXfv3nj77bcxZcoUj5SblMeu1UPcCB43fq40VcJoNsJoNlrGgNRlQS2B2lf1dLa0uNynrPTFtWpiOy6hpEIKJsX6YhRdL8KvV37Ftz99i1KjdUppib4ExRXFlkGS1wzX6l2GE7+daICaNBLvHD5WZ31j+qJ7VHdLEKnaMmL7s7/WX5HhvqFVDSa2v89sN8AaWG/81oJapbZsKpUKGpUGvhpfaNVay2a5v8rj1Sp1/cbwNACPv/qQIUOg0+mwYcMGTJ8+HUuXLsXtt98OjUaD4uJiBAcHQ6Ox/pJv3749cnJy7J7jd7/7HT788EOkpKR4uPTUXMgre5qEqdrPRpMRBrPBcmE221BjS6PWQKPS2AUPH5VPtVDireTFtmwDiRw+bFtNLPts9uv0OhhMBudPft61MsizNsL8w6QvMP9Q6Cv1+ObcN7Ue+6eBf0K3qG4AUK0ly3KOUX2mkqOWL9uZS7b3OfrZtrvP8pw37hMmgWMZx9CtbzdoNBqHz1OtPDW8hit1clZWR+Vz9hpVX8+V963a+wHAbDLj8PeHYUg04MHPHnR67mSLf7cYg+IG1fq4lqjaCsdVWkpqajGxDSXyf/00fnbBxFEgqRpolPb7r0nG0Kxbtw6TJ09GWloa1Go19u7dCwAIDw9HRkaGXVDRarXVBv9qtVrExsaiVatWnis4eUTVlhTbsGKolEKKwWxwGFTksSPylFCNSgONWgMflY/dNFFvUlFZ4TCQ6PQ6FFcUOwwktutb1LfLQR6XEOofapmlYSo1ISE2AeEB4Zb7QvxCEOZnDS1h/mEI9g2Gj6Z6c7PJbMIt626pccpoTHAM5t4yt1mOoTEHmdGnbcsYQ1FXJpUJvmpfDIgbgJhWMbWew1va39IEpWx4cvgwmqSmuXJjOVRmVbWwUpWjkOGn8YNGpYFWrbX8jnMWRmw3b9Ak7UPjx4/H6dOncejQIaSmplrWlXF1wtXZs2cbsXTUGOR/tCazCXqjNMVRp9dBVamSQkqlAUazsVqIsR3gqlapra0qanW9g4oS1r8wCzOuGa5ZW0RsWkAsXTRVxpjYLspVYar/+hYB2gCE+oVKoeRG+Aj1C7Xss4QQm0Ai3xfkE2TXimCqNOF/3/4PfYf0dfsLXaPW4Pnbnsdjnz/mdMrokmFLmt25JCulnsNqY0xsx8ZV2QfA7neXWqWGMN3Yr1LBR+1j12JiG0wcBRJvCibuarIOr+joaIwdO7apXp4aiG1QqdoFZDQbYTRJm22Li7yuwAXdBai1aktQkf/B+mp97bqCGoOjy97HtIrB87c9jzGdxjToaxlMBrtAUlRWhMyiTGQdyZLGkdi0oFQNJDqDzmGzcl2ooKoWPuQWEdt9VUOK3Erip60+wL6pjek0Bu+Me6f6OQyOwZJhSxr8HFLDa8pz6Kj7pmowMQuzXXcZYA0mtgPztSottBqbMSZq5904pkoTjuM44kPjnU6EIffx4pTkkBDC4WBak9mESrM0oNZQaajWNSTPnrDtn5XDio/aB/5afwiN9FdKUw2KdXbZ+4JrBXjs88fwzrh37H6ZCiEsU0cdjiOx7dKxaTHRVUj7nK4Ces71Mvtr/B0GEksYsQkkVVtJWvm2apF/2Y3pNAYjk0bix/wfUXC9AG2C2uDmdjdDq9Gi0lxpeVzVLyVXVv8lzxjTaQxGJY9yu6XUnZk5AgJqVO+i0aq00Gg0ltYS2wGwdo91MHjWVUaz9MccP2eNg4HGy9jO/KnaqmIym2AwG2A0STN/bFtf7JqEb4x+l/9B+2h84KeV+nVd+YdqMtd/zQh3XTdcx5/3/Nlhv7287487/ogurbvYhZT6tpIAsFvtU12hRmzbWLtuHMvAV79Qu0Aiz+DwBo6a9C2fQ2Gq1i2tggq92/ZGiioFACxh25az6ypVvc/R/XVR43pAN26LSun5i8uLq03Zr/p4oPoXn+39Nd3XEPc35HPJ98v/9k1mk92Vp1NjUy3nWj6HzsKK7Ws4ChdqlbpOM3PcCSbUPDHQtBCuTlE2moyW1hc5qMi/SOVfBnJYkf9ScTWoNJVyYzmulF3BletXUFhWKP1cdgWF16Wf5X2FZYXQ6WtfpElv0uPI5SPV9vtqfKu3gPg5DiQh/vZdOsG+wZa/OhtiHIkSOPpCkq82rdPrAKP9tFHA+SBIR19OtqFank1T18BS0/31OdbZ/ZWVlTiDM4gJibGbzenotasGsfrcb3txTcB6cU5n99d0AU4ADls9nD3e9j55af3rhuvQmDV299v+DnJ07m3Pd0uamUMNh4FGAZxNUTYLMwyVhjpPUdaoNfBV+zbrQWbXDdedB5Pr1tBy5fqVBrvSrK1Z/WdhdPJou/Di7etc1NZ6YvuZc/bXs1Yl/coJ9QuFv69/tRkajmZstCTy+LFQv9BmsaikM40V9IxGI07iJBLCEixX27a9vyWfe2p8DDRNSJ7G5yisyINpDWaD1KJi0+ICKG+KsjwO5UrZFVwqvYSfi39G1pEs/Fbxm8OQUl5ZXqfn99P4ITIwElGBUYgMkv4bFRQl3Q603j5TdAbTP6v9yu7DE4djQPsB7la32atp7EHVNS7caT2p2oIib5WVlchCFtq2atusv9C9XY1dSPXI9CqzdLCv1hc+Wp5/algMNI3AduxJ1S6gSnMlyiukL+tzxecANWqcoix/Efhp/Sz7mgshBHR6ncPWE0vXz3VrK0u1KcRna35+f62/NZDcCCdyMKkaXoJ9g11qPUkMS2yR61/U1HriaPyBs0GRtrM1vK31hIiUjYGmnvSVepQZy5xOUbZc18dm5o/dWgRan0afolwXQggUVxTXOBZFDim/lf0GvUlfp+cP9AlEZEAkAioDkBiTaG1FkVtVbAJM1TVMGoIS1r9wpfWk6oUAq7aG1NZ64qgFpTl8/oiI3MVAU0/lleXI1+Vbxqho1BqooIKPRpqi7OiLQh4Y56/1rzYwsDGYhRnFFcXW1pKqY1Fu7JdDStVZIrVp5duqWsuJbUix7fIJ9Als8kGxnl7/otrAWKM0MLZUXwpVpcquGxGQglXVAa+1tZ44akUhIvImDDT1YDKb8H3u9zh65SgSwxM9utKsyWxCUUWRw5ByueyyXavKb+W/2a3L4YpQv9Bq3Tq2wcRyX2AkAnwCGqmWjcfd9S9cbT0BrAFFDXW1VUABINgvGH6+fk7Xu7BtRWHrCRFRzRho3LTt6DbM2zUP+bp8y776rjRbaa7E1fKr1bp5Ll+/bA0t160hpa5ro4T5h1Ubk1JtIG1gFFoHtvaKdU80ag1SY1Ot11kxG2EwGRwOjLVVNWjUtfWk0liJbGQjulU0B8YSETUQBho3bDu6DRO3THRppVmjyYjfyn+zhBF5lk/2+Wxs/O9GFJYXWsLL1fKrdV7YKyIgwmkwsQ0urQNbw1fTspfarkvriazqisaujD2pb+sJW1uIiBoeA00dmcwmzNs1r8aVZmfvmI340HgUlhWiqKLI+ZNdqb5LBRVaB7Z2GFJsu3zkkKJVt9xTWDWcOJrJY8vZuieutJ5wcCwRkbK13G/DRvJd7nd23UyOGEwGnLx60nJbo9KgdWBrSyBpHdAa5t/M6NGlB9q0aoM2QW0s90UERDSrqdkNxTaIGCulQcfXDdehMqlq7NqpulVd0ry21UMZToiIvAMDTR1dLL1Y+4MAzLl5Du7uejeiAqMQHhBuN+vEMsunrzKXvndnWrHtwFi5ZcVP62cZFFtT1w7XPSEiotow0NRRTHCMS48bEj8EXSO7NnJp6k8OHlWvmN1YXTsatQamShOO4ihiQ2I5KJaIiBoEA00dDe4wGLEhsTivO98sV5p1ZcXYqhwFD3lgrI/ap8HHnQiV+1c0JiIicoSBpo40ag1WjV6FiVsmNvpKs7V17chXy7Z97bpeb4ddO0RE1BIw0LhhQrcJ2Hrf1urr0NSw0qxtOJEHxZYZy6Ayqxq0a4fX2yEiIm/EQOOmCd0m4K4ud2HnqZ3IvpKN9sHt0S+mH1QqFUoqSuy6dmyv46RWqSHMUnDRqDTw1/pzSjEREVE9MdDUg0atwZD4IegW2U1qPbHp1qmpa8dUacJxHEd8WDwHxRIRETUABpp6CvELQSvfVnXq2qnrxR+JiIioZhxg0QA4ToWIiKhp8ZuYiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFE/b1AXwBCEEAECn0zVxSSRGoxFlZWXQ6XTw8fFp6uJ4HOvvvfX35roDrD/r7731d7fu8ve2/D1eE68INKWlpQCAuLi4Ji4JERER1VVpaSlCQ0NrfIxKuBJ7FM5sNuPChQsIDg6GSqVq6uJAp9MhLi4OeXl5CAkJaerieBzr77319+a6A6w/6++99Xe37kIIlJaWol27dlCrax4l4xUtNGq1GrGxsU1djGpCQkK87kNti/X33vp7c90B1p/19976u1P32lpmZBwUTERERIrHQENERESKx0DTBPz8/PDcc8/Bz8+vqYvSJFh/762/N9cdYP1Zf++tvyfq7hWDgomIiKhlYwsNERERKR4DDRERESkeAw0REdVLcXExfvrpJxQVFTV1UTzOm+ve3DDQNIK5c+dCpVJZto4dOwIAsrKyMGDAAISHhyMtLc1uKedvvvkG3bp1Q2RkJJYvX95URXdbYWEhEhMTcfbsWcs+d+u7detWxMfHo127dti8ebOnqlAvjurv7HMAtKzPwmeffYakpCRotVqkpKTg6NGjALzn/Durv7ec/3/9619ISEjAjBkzEBsbi3/9618AvOP8O6u7t5x7W6NHj8bGjRsBuH9+V69ejbZt2yIpKQl79uypeyEENbiBAweK//znP6KoqEgUFRUJnU4nKioqREJCgpg5c6Y4deqUGDNmjPh//+//CSGEuHz5sggJCRFLliwRJ06cEH379hV79uxp4lq47sqVK+KWW24RAEROTo4QQrhd319++UX4+vqKtWvXiiNHjoiOHTuKY8eONVXVXOKo/kI4/hwI4f570xydOnVKhIeHi48++kgUFBSI3//+92LQoEFec/6d1V8I7zj/xcXFIjIyUmRmZgohhNiwYYOIj4/3ivPvrO5CeMe5t/XPf/5TABAbNmxw+/zu2rVL+Pv7i08//VT88MMPIjExURQWFtapHAw0DcxoNIqQkBBRWlpqt/+TTz4R4eHh4vr160IIIQ4fPixuvfVWIYQQK1asEF27dhVms1kIIcSnn34qHnjgAc8WvB6GDx8uVq1aZfeF7m59582bJ0aNGmV57pUrV4o///nPHqxN3Tmqv7PPgRAt67Pw+eefizVr1lhu79mzRwQEBHjN+XdWf285/7m5ueKf//yn5XZmZqZo1aqVV5x/Z3X3lnMv++2330Tbtm1Fly5dxIYNG9w+v3fddZeYOXOm5b758+eLtWvX1qks7HJqYL/88gvMZjNSUlIQEBCA0aNHIzc3F5mZmUhNTUVgYCAAoHfv3sjOzgYAZGZm4rbbbrNcZ+rmm2/GoUOHmqwOdbV27VrMnTvXbp+79c3MzMT//d//WZ5HCe+Fo/o7+xwA7r83zdGdd96Jxx57zHL7+PHj6NSpk9ecf2f195bzHxcXhwceeACAdDXlFStW4J577vGK8++s7t5y7mULFy7EPffcg9TUVADun9+GOPcMNA0sOzsbXbp0wfvvv48jR45Aq9Xiscceg06nQ2JiouVxKpUKGo0GRUVF1e4LCQnBhQsXmqL4brEtu8zd+irxvXBUf2efA8D996a5MxgMeO211zBr1iyvOv8y2/p72/nPzMxEdHQ0du3ahddff92rzn/VunvTuf/666/x1VdfYdmyZZZ97p7fhqi/V1yc0pMeeOABS2oHgDfffBOJiYno1q1btRUS/f39UVZWBq1Wa3efvF/JqtYJcK2+LeW9cPY50Ol0br83zd1zzz2HoKAgzJgxA3/5y1+87vzb1t/Hx8erzn/v3r3xxRdf4Mknn8SMGTOQnJzsNee/at23bt3qFee+oqICM2fOxFtvvYXg4GDLfnfPb0PUny00jaxNmzYwm82Ijo7GlStX7O4rLS2Fr68vIiIi7O6T9ytZ1ToBrtW3Jb4XgPVzcPHiRbffm+Zsz549WL16NTZt2gQfHx+vO/9V619VSz//KpUK/fr1w7vvvott27Z51fmvWvfi4mK7+1vquX/hhRcwYMAAjB071m6/u+e3IerPQNPA0tLSsGnTJsvt/fv3Q61Wo1evXti/f79lf05ODvR6PSIiIjBgwAC7+zIyMtC+fXuPlruhVa2Tq/VtKe+Fs89BXFyc2+9Nc5WTk4PJkydj9erV6N69OwDvOv+O6u8t5/+bb75BWlqa5bavry9UKhW6devW4s+/s7ovWbLEK879pk2b8NlnnyEsLAxhYWHYtGkTnnjiCbz77rtund8GqX99RziTvffff18kJiaKL7/8Uvz3v/8VnTt3FtOmTRNGo1FERUVZpujNmDFD3HnnnUIIadqvv7+/2L17tzAYDGL06NHij3/8Y1NWwy2oMsvHnfoePnxYBAUFiSNHjojS0lKRkpIi/v73vzdJferKtv7OPgdCuP/eNEdlZWWie/fu4tFHHxWlpaWWzWAweMX5d1b/9957zyvO/4ULF0RISIhYs2aNyM3NFVOnThWjR4/2in//zuruLf/28/LyRE5OjmW79957xauvvur2+f3ss89ETEyMyM/PFwUFBaJ9+/Zi69atdSoTA00jWLRokQgNDRURERFi7ty54tq1a0II6YQFBgaK1q1bi6ioKPHrr79ajnnrrbeEj4+PCA8PF4mJiaKgoKCpiu82VFmHxd36PvPMM8LX11eEhISIfv36ibKyMk9Ww21V6+/scyBEy/ksfPrppwJAtS0nJ8crzn9N9feG8y+EEF988YXo3r27CA4OFhMnThSXL18WQnjHv39ndfeWc2/r4YcfFhs2bBBCuHd+zWazePDBB0VAQIAICAgQd955p2Xqt6t4tW0PKygowKFDh5CamorWrVvb3ZeTk4Njx45h8ODBaNWqVROVsGG5W9/s7GycP38eQ4cObdb9yPXhDZ8Fnn/neP699/x7w7l39/weOHAA169fx9ChQy1Tv13FQENERESKx0HBREREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRERESkeAw0REREpHgMNERERKR4DDRE1CiOHDmCnj17IiIiAk8++SS6du2KN954AwDw2WefoUuXLggKCsLw4cNx4cIFAEBCQgJmzZqF0NBQLFy4EHfccQdat26NAwcOAAB27dqFXr16ISwsDDNmzIBer6+1HOnp6Zg2bRqef/55hIWFITExET/88IPdfbK9e/ciISEBgHQV5Tlz5qBVq1ZYunQp+vfvj9jYWJw7d64B3yUiaigMNETUKGbNmoXJkyfj66+/xvr167F+/Xo8+OCDKCoqwv3334/Fixfj1KlTaNOmDV588UXLcTqdDq+++iqWL1+OWbNmISUlBV988QVOnTqFu+66C/PmzcOBAwfw888/49VXX3WpLDt27MCZM2eQkZGBW2+9FYsXL3bpuMDAQCxYsADp6en4xz/+gaCgIHz//fduvR9E1LgYaIioURw+fBi///3v0adPH/To0QO5ubkIDw9Hq1atcO7cOUyaNAmnT5/G9evXcfz4cctxU6dORefOndG2bVvcddddiIuLg9FoxEcffYSUlBTMmDEDnTp1whNPPIHt27e7VBatVos1a9YgMTERU6dORV5enkvHTZ8+HUlJSejbty9SU1MRExMDo9Ho1vtBRI1L29QFIKKWqWPHjti/fz8iIyNx8uRJdO/eHQAghMCiRYuwfft2dOvWDcHBwTCZTJbj/P397f4ry8/PR0ZGBsLCwgAAlZWVLl+8LzU1FX5+fgAAX19fOLuEXVlZmd1tZ2UhouaHLTRE1OCEEOjevTvmzp2L6OhoTJ06FX369AEAbNq0CT/++CPOnTuH77//HuPGjXPpOWNjYzFu3DgcPnwYhw8fRmZmJnbv3u3SsSEhIQ73q1QqmM1my+1Dhw659HxE1Pww0BBRgzt+/Di+++47/PDDDzh9+jSWL19uua+0tBRCCFy9ehU7d+7ECy+84LTFxNakSZPw3Xff4eTJk/Dz88Mbb7yB6dOn16uc7du3x6FDh2A0GnHq1CmsWbOmXs9HRE2HgYaIGlznzp3Rpk0bDB06FImJiQgICMCsWbMAAA8//DASEhLQrVs3LFmyBDNnzsTRo0dRUVFR43MmJyfjvffew4IFC9CxY0ccOXIEmzdvrlc5J0+ejPbt26NLly6YPn06/vrXv9br+Yio6aiEK38aERHVwfr167FlyxasW7cOgYGBOHLkCMaMGYNLly457f4hIqoPDgomogZ32223YdOmTejZsyfKy8sRHx+Pl19+mWGGiBoNW2iIiIhI8TiGhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFI+BhoiIiBSPgYaIiIgUj4GGiIiIFO//A5H9OcGogVqHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plot_learning_curve(lgb_model, \"LGBM\", tr_x, tr_y, ylim=None, cv=None, n_jobs=1)\n",
    "plot_learning_curve(xgb_model, \"XGBOOST\", tr_x, tr_y, ylim=None, cv=None, n_jobs=1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "553266db-83b0-4122-b22e-9966000c1797",
   "metadata": {},
   "source": [
    "结果图上可以看出，随着数据量的增加，BP模型虽然趋近于收敛，但是在训练集和检验集上准确度表现都很差，。这预示着存在着很高的偏差，是欠拟合的表现。\n",
    "\n",
    "逻辑回归\\决策树\\随机森林\\xgboost\\lgbm出现了高方差情形，也就是过拟合的情况。这都预示着我们要找到正确率低原因，并且优化我们的模型。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8206d90f-e6e9-4b6f-89ba-8244833a2c1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def GRA_ONE(DataFrame,m=-1):\n",
    "    gray= DataFrame\n",
    "    # 读取为df格式\n",
    "    gray=(gray - gray.min()) / (gray.max() - gray.min())\n",
    "    # 标准化\n",
    "    std = gray.iloc[:, m]  # 为标准要素\n",
    "    ce = gray.iloc[:, 0:]  # 为比较要素\n",
    "    n=ce.shape[0]\n",
    "    m=ce.shape[1]# 计算行列\n",
    "\n",
    "    # 与标准要素比较，相减\n",
    "    a=zeros([m,n])\n",
    "    for i in range(m):\n",
    "        for j in range(n):\n",
    "            a[i,j]=abs(ce.iloc[j,i]-std[j])\n",
    "\n",
    "    # 取出矩阵中最大值与最小值\n",
    "    c=amax(a)\n",
    "    d=amin(a)\n",
    "\n",
    "    # 计算值\n",
    "    result=zeros([m,n])\n",
    "    for i in range(m):\n",
    "        for j in range(n):\n",
    "            result[i,j]=(d+0.5*c)/(a[i,j]+0.5*c)\n",
    "\n",
    "    # 求均值，得到灰色关联值\n",
    "    result2=zeros(m)\n",
    "    for i in range(m):\n",
    "            result2[i]=mean(result[i,:])\n",
    "    RT=pd.DataFrame(result2)\n",
    "    return RT\n",
    "\n",
    "def GRA(DataFrame):\n",
    "    list_columns = [str(s) for s in range(len(DataFrame.columns)) if s not in [None]]\n",
    "    df_local = pd.DataFrame(columns=setcols)\n",
    "    for i in range(len(DataFrame.columns)):\n",
    "        df_local.iloc[:,i] = GRA_ONE(DataFrame,m=i)[0]\n",
    "    return df_local\n",
    "play_score = GRA(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "73cc1051-b9c7-4a8c-be15-7a5928d7541a",
   "metadata": {},
   "outputs": [],
   "source": [
    "play_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3ba090df-9777-4bf1-8282-ac7387b9fd31",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def ShowGRAHeatMap(DataFrame):\n",
    "    colormap = plt.cm.hsv\n",
    "    ylabels = DataFrame.columns.values.tolist()\n",
    "    f, ax = plt.subplots(figsize=(15, 15))\n",
    "    ax.set_title('Wine GRA')\n",
    "    # 设置展示一半，如果不需要注释掉mask即可\n",
    "    mask = np.zeros_like(DataFrame)\n",
    "    mask[np.triu_indices_from(mask)] = True  # np.triu_indices 上三角矩阵\n",
    " \n",
    "    with sns.axes_style(\"white\"):\n",
    "        sns.heatmap(DataFrame,\n",
    "                    cmap=\"YlGnBu\",\n",
    "                    mask=mask,\n",
    "                    )\n",
    "    plt.savefig('./ans2/灰色关联热力图_语音.jpg')\n",
    "    plt.show()\n",
    "ShowGRAHeatMap(play_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cf045bf-5fa4-4767-934c-9603f5c8fa5a",
   "metadata": {},
   "source": [
    "统计出每个特征关联度的均值后，我们发现大部分的特征关联度都在0.4与0.9之间，也就是说大部分特征都与结果呈现出了相对较高的关联性。\n",
    "这也意味着已有的数据源的特征关联度对之前模型的影响是有限的。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e4a0f85c-e303-4b90-9507-40bd6e62756b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "!{sys.executable} -m pip install hyperopt -i https://pypi.tuna.tsinghua.edu.cn/simple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3ad0b81-1fac-4cb6-94cf-e729bbf20da8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from hyperopt import fmin, tpe, hp, STATUS_OK, Trials\n",
    "#基于TPE算法进行全局寻优\n",
    "\n",
    "a=[]\n",
    "b=[]\n",
    "def hyperopt_train_test(params): \n",
    "    clf = RandomForestClassifier(**params)\n",
    "    clf.fit(tr_x,tr_y)\n",
    "    y_pred = clf.predict(te_x)\n",
    "    pj=f1_score(te_y,y_pred,average=\"micro\")\n",
    "    a.append(pj)\n",
    "    b.append(params)\n",
    "    return pj\n",
    " \n",
    "space = {\n",
    "    'n_estimators': hp.choice('n_estimators', range(1,500,5)),\n",
    "    'max_depth': hp.choice('learning_rate',  range(1,50)),\n",
    "    'min_samples_split': hp.choice('min_samples_split', range(2,50)),\n",
    "    'min_samples_leaf': hp.choice('min_samples_leaf', range(1,20))}\n",
    " \n",
    "def f(params):\n",
    "    acc = hyperopt_train_test(params)\n",
    "    return {'loss': -acc, 'status': STATUS_OK} #注意这里的负号\n",
    " \n",
    "trials = Trials()\n",
    "best = fmin(f, space, algo=tpe.suggest, max_evals=100, trials=trials)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f8d151a2-ff34-4b12-8abf-7406edabc446",
   "metadata": {},
   "outputs": [],
   "source": [
    "max_f1_dict=b[a.index(max(a))]\n",
    "print(max_f1_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a9f059c0-f4d4-4376-9de0-06133fd0a92c",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"\\n随机森林:\")\n",
    "rf=RandomForestClassifier(**max_f1_dict)\n",
    "rf.fit(tr_x,tr_y)\n",
    "print(\"训练集准确度:{:.3f}\".format(rf.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(rf.score(te_x,te_y)))\n",
    "y_pred = rf.predict(te_x)\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "caa77ed7-fc29-46c8-b3c1-033e86a63e59",
   "metadata": {},
   "outputs": [],
   "source": [
    "rf=RandomForestClassifier(**max_f1_dict)\n",
    "rf.fit(X,YY)\n",
    "y_pred = rf.predict(test_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e9a0c03c-c099-44a1-b8cb-1d9141919f82",
   "metadata": {},
   "outputs": [],
   "source": [
    "result=pd.read_excel('./ans2/result.xlsx',sheet_name='上网')\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b35a63b-fe55-4827-b25b-93529c7d28dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "result['手机上网整体满意度']=y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "015c16ab-e69a-495e-b551-4b749f3b4445",
   "metadata": {},
   "outputs": [],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35423f10-99f8-454b-89df-70bb4ef25f75",
   "metadata": {},
   "outputs": [],
   "source": [
    "YY=Y2\n",
    "DT=DecisionTreeClassifier( criterion='entropy')\n",
    "\n",
    "see1=DT.fit(X,YY)\n",
    "\n",
    "y_pred=DT.predict(X)\n",
    "\n",
    "print(classification_report(y_pred,YY))\n",
    "\n",
    "\n",
    "# 重要性\n",
    "features_import = pd.DataFrame(X.columns, columns=['feature'])\n",
    "features_import['importance'] = DT.feature_importances_  # 默认按照gini计算特征重要性\n",
    "allcol=dinglei+dingliang\n",
    "def getcol(x):\n",
    "    for i in allcol:\n",
    "        if i in x:\n",
    "            return i\n",
    "\n",
    "features_import['feature']=features_import['feature'].apply(lambda x:getcol(x))\n",
    "features_import=features_import.groupby('feature').sum().reset_index(drop=False)\n",
    "features_import.sort_values('importance', inplace=True)\n",
    "# 绘图\n",
    "from matplotlib import pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 显示中文黑体\n",
    "# plt.rcParams['axes.unicode_minus'] = False # 负值显示\n",
    "fig, ax = plt.subplots(figsize=(15, 10))\n",
    "\n",
    "plt.barh(features_import['feature'], features_import['importance'], height=0.7, color='#008792', edgecolor='#005344') # 更多颜色可参见颜色大全\n",
    "plt.xlabel('feature importance') # x 轴\n",
    "plt.ylabel('features') # y轴\n",
    "plt.title('网络覆盖与信号强度——上网业务 Feature Importances') # 标题\n",
    "for a,b in zip( features_import['importance'],features_import['feature']): # 添加数字标签\n",
    "    plt.text(a+0.001, b,'%.3f'%float(a)) # a+0.001代表标签位置在柱形图上方0.001处\n",
    "plt.savefig('./ans2/网络覆盖与信号强度—上网业务featureimportance')\n",
    "plt.show()\n",
    "\n",
    "tr_x,te_x,tr_y,te_y=train_test_split(X,YY,test_size=0.3,random_state=5)\n",
    "\n",
    "print(\"\\n随机森林:\")\n",
    "rf=RandomForestClassifier(**max_f1_dict)\n",
    "rf.fit(tr_x,tr_y)\n",
    "print(\"训练集准确度:{:.3f}\".format(rf.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(rf.score(te_x,te_y)))\n",
    "y_pred = rf.predict(te_x)\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))\n",
    "\n",
    "\n",
    "rf=RandomForestClassifier(**max_f1_dict)\n",
    "rf.fit(X,YY)\n",
    "y_pred = rf.predict(test_X)\n",
    "result['网络覆盖与信号强度']=y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0561d5cb-646d-40b2-82ed-d58cea0efbe4",
   "metadata": {},
   "outputs": [],
   "source": [
    "YY=Y3\n",
    "DT=DecisionTreeClassifier( criterion='entropy')\n",
    "\n",
    "see1=DT.fit(X,YY)\n",
    "\n",
    "y_pred=DT.predict(X)\n",
    "\n",
    "print(classification_report(y_pred,YY))\n",
    "\n",
    "# 重要性\n",
    "features_import = pd.DataFrame(X.columns, columns=['feature'])\n",
    "features_import['importance'] = DT.feature_importances_  # 默认按照gini计算特征重要性\n",
    "allcol=dinglei+dingliang\n",
    "def getcol(x):\n",
    "    for i in allcol:\n",
    "        if i in x:\n",
    "            return i\n",
    "\n",
    "features_import['feature']=features_import['feature'].apply(lambda x:getcol(x))\n",
    "features_import=features_import.groupby('feature').sum().reset_index(drop=False)\n",
    "features_import.sort_values('importance', inplace=True)\n",
    "# 绘图\n",
    "from matplotlib import pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 显示中文黑体\n",
    "# plt.rcParams['axes.unicode_minus'] = False # 负值显示\n",
    "fig, ax = plt.subplots(figsize=(15, 10))\n",
    "\n",
    "plt.barh(features_import['feature'], features_import['importance'], height=0.7, color='#008792', edgecolor='#005344') # 更多颜色可参见颜色大全\n",
    "plt.xlabel('feature importance') # x 轴\n",
    "plt.ylabel('features') # y轴\n",
    "plt.title('手机上网速度 Feature Importances') # 标题\n",
    "for a,b in zip( features_import['importance'],features_import['feature']): # 添加数字标签\n",
    "    plt.text(a+0.001, b,'%.3f'%float(a)) # a+0.001代表标签位置在柱形图上方0.001处\n",
    "plt.savefig('./ans2/手机上网速度featureimportance')\n",
    "plt.show()\n",
    "\n",
    "\n",
    "tr_x,te_x,tr_y,te_y=train_test_split(X,YY,test_size=0.3,random_state=5)\n",
    "\n",
    "print(\"\\n随机森林:\")\n",
    "rf=RandomForestClassifier(**max_f1_dict)\n",
    "rf.fit(tr_x,tr_y)\n",
    "print(\"训练集准确度:{:.3f}\".format(rf.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(rf.score(te_x,te_y)))\n",
    "y_pred = rf.predict(te_x)\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))\n",
    "\n",
    "\n",
    "rf=RandomForestClassifier(**max_f1_dict)\n",
    "rf.fit(X,YY)\n",
    "y_pred = rf.predict(test_X)\n",
    "result['手机上网速度']=y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "766dcb8b-051e-4c4a-9ef0-a9ec355e69fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "YY=Y4\n",
    "DT=DecisionTreeClassifier( criterion='entropy')\n",
    "\n",
    "see1=DT.fit(X,YY)\n",
    "\n",
    "y_pred=DT.predict(X)\n",
    "\n",
    "print(classification_report(y_pred,YY))\n",
    "\n",
    "\n",
    "\n",
    "# 重要性\n",
    "features_import = pd.DataFrame(X.columns, columns=['feature'])\n",
    "features_import['importance'] = DT.feature_importances_  # 默认按照gini计算特征重要性\n",
    "allcol=dinglei+dingliang\n",
    "def getcol(x):\n",
    "    for i in allcol:\n",
    "        if i in x:\n",
    "            return i\n",
    "\n",
    "features_import['feature']=features_import['feature'].apply(lambda x:getcol(x))\n",
    "features_import=features_import.groupby('feature').sum().reset_index(drop=False)\n",
    "features_import.sort_values('importance', inplace=True)\n",
    "# 绘图\n",
    "from matplotlib import pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 显示中文黑体\n",
    "# plt.rcParams['axes.unicode_minus'] = False # 负值显示\n",
    "fig, ax = plt.subplots(figsize=(15, 10))\n",
    "\n",
    "plt.barh(features_import['feature'], features_import['importance'], height=0.7, color='#008792', edgecolor='#005344') # 更多颜色可参见颜色大全\n",
    "plt.xlabel('feature importance') # x 轴\n",
    "plt.ylabel('features') # y轴\n",
    "plt.title('手机上网稳定性 Feature Importances') # 标题\n",
    "for a,b in zip( features_import['importance'],features_import['feature']): # 添加数字标签\n",
    "    plt.text(a+0.001, b,'%.3f'%float(a)) # a+0.001代表标签位置在柱形图上方0.001处\n",
    "plt.savefig('./ans2/手机上网稳定性featureimportance')\n",
    "plt.show()\n",
    "\n",
    "tr_x,te_x,tr_y,te_y=train_test_split(X,YY,test_size=0.3,random_state=5)\n",
    "\n",
    "print(\"\\n随机森林:\")\n",
    "rf=RandomForestClassifier(**max_f1_dict)\n",
    "rf.fit(tr_x,tr_y)\n",
    "print(\"训练集准确度:{:.3f}\".format(rf.score(tr_x,tr_y)))\n",
    "print(\"测试集准确度:{:.3f}\".format(rf.score(te_x,te_y)))\n",
    "y_pred = rf.predict(te_x)\n",
    "print(\"平均绝对误差:\",mean_absolute_error(te_y, y_pred))\n",
    "print(\"ACC\",accuracy_score(te_y,y_pred))\n",
    "print(\"REC\",recall_score(te_y,y_pred,average=\"micro\"))\n",
    "print(\"F-score\",f1_score(te_y,y_pred,average=\"micro\"))\n",
    "\n",
    "\n",
    "rf=RandomForestClassifier(**max_f1_dict)\n",
    "rf.fit(X,YY)\n",
    "y_pred = rf.predict(test_X)\n",
    "result['手机上网稳定性']=y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40960f89-7d6b-4c64-b054-5d5ba2fab0d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "result.to_excel('result_上网.xlsx',index=None)"
   ]
  }
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